DETAILED ACTION
Claims 5,7,8 objected to because of the following informalities:
Claims 1–20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1–20 of U.S. Patent No. 11,461,966.
Claims 1–20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1–20 of U.S. Patent No. 12,236,528 B2.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Perez et al. (US 2015/0153835 A1 plus US 9,645,654 B2) with Related U.S. Application Data Provisional application No. 61/911,975, filed on Dec. 4, 2013.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 9,785,247 B1) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2018/0032144 A1 plus corresponding US 9,983,686 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2019/0033975 A1 plus corresponding US 10,429,943 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2020/0033951 A1 plus corresponding US 10,936,082 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2021/0181859 A1 plus corresponding US 11,586,292 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2023/0205321 A1 plus corresponding US 11,914,792 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2024/0201794 A1 plus corresponding US 12,314,478 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2025/0390178 A1) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Matinez del Rincon (Feature-based human tracking: from coarse to fine):
Claim Objections
Claims 5,7,8 objected to because of the following informalities:
Claim 5 is missing an article (“a” or “the”) for claim 5’s “construct”. Claim 5’s “construct” is interpreted as “the construct” referring to claim 1’s “construct”.
Claim 7 references claim 1’s “improving of the conformance”; however, claim 7 does not have “improving of the conformance”. Thus claims 7,8 is interpreted to depend on claim 2’s “improving conformance”.
Thus claim 8 rejected.
Appropriate correction is required.
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35 USC § 101 – Positive Statement
Claim 1 reflects a disclosed improvement in the function of a computer via [00139] 2nd S:
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Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/forms/. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1–20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1–20 of U.S. Patent No. 11,461,966.
Regarding Claims 1–20: The following table illustrates the correspondence between the claimed limitation of 1–120 of the current application and the claimed limitation of 1–20 of 11,461,966 Patent.
19/021,044 (instant app)
11,461,966 (U.S. Patent)
1. A method of accurately capturing gestural motion of a control object in a three- dimensional (3D) sensory space, the method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determining of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
2. The method of claim 1, further including:
responsive to modifications in the observation information based on another image captured at time tl, wherein the control object moved between tO and tl, improving conformance of the 3D solid model to the modifications in the observation information.
1. A method of accurately capturing gestural motion of a control object in a three-dimensional (3D) sensory space, the method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time to, the determining of the observation information including:
identifying a contour of the control object, the identified contour having a plurality of contour points;
identifying a first unmatched contour point of the plurality of contour points;
determining a normal for the first unmatched contour point;
identifying a second unmatched contour point of the plurality of contour points by locating an unmatched contour point that is closest to the first unmatched contour point and is reachable by a line having a most opposite normal to the normal for the first unmatched contour point;
defining a span as a shortest distance between the first unmatched contour point and the second unmatched contour point;
defining a span length as a length of the defined span; and
determining the observation information to include the defined span and the defined span length;
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time t0; and
responsive to modifications in the observation information based on another image captured at time t1, wherein the control object moved between t0 and t1, improving conformance of the 3D solid model to the modifications in the observation information.
3. The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of closed curves to at least a portion of a construct of the control object.
2. The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of closed curves to at least a portion of a construct of the control object.
4. The method of claim 3, wherein the set of closed curves includes at least one of radial solids, capsuloids, spheres, ellipsoids, and hyperboloids.
3. The method of claim 2, wherein the set of closed curves includes at least one of radial solids, capsuloids, spheres, ellipsoids, and hyperboloids.
5. The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of capsuloids to at least a portion of construct of the control object.
4. The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of capsuloids to at least a portion of construct of the control object.
6. The method of claim 1, wherein the control object is a hand and the fitting the one or more 3D solid subcomponents further includes at least one of:
fitting capsuloids to finger portions of a construct of the control object; and
fitting radial solids to palm and/or wrist portions of the construct.
5. The method of claim 1, wherein the control object is a hand and the fitting the one or more 3D solid subcomponents further includes at least one of:
fitting capsuloids to finger portions of a construct of the control object; and
fitting radial solids to palm and/or wrist portions of the construct.
7. The method of claim 1, wherein the improving of the conformance of the 3D solid model includes altering the 3D solid subcomponents to conform to at least one of length, width, orientation, and arrangement of portions of a construct of the control object.
6. The method of claim 1, wherein the improving of the conformance of the 3D solid model includes altering the 3D solid subcomponents to conform to at least one of the defined span length, width, orientation, and arrangement of portions of a construct of the control object.
8. The method of claim 7, wherein the altering of the 3D solid subcomponents further includes applying a transformation matrix to a plurality of points on the 3D solid subcomponents.
7. The method of claim 6, wherein the altering of the 3D solid subcomponents further includes applying a transformation matrix to a plurality of points on the 3D solid subcomponents.
9. The method of claim 1, wherein the constructing of the 3D solid model further includes determining the 3D solid subcomponents from physical characteristics of a type of control object being observed.
8. The method of claim 1, wherein the constructing of the 3D solid model further includes determining the 3D solid subcomponents from physical characteristics of a type of control object being observed.
10. The method of claim 9, wherein the control object is a hand and the physical characteristics of the hand include at least one of:
four fingers and a thumb of the hand;
a palm to which the fingers and the thumb are connected; and
positions and angles of the fingers and the thumb relative to each other and to the palm.
9. The method of claim 8, wherein the control object is a hand and the physical characteristics of the hand include at least one of:
four fingers and a thumb of the hand;
a palm to which the fingers and the thumb are connected; and
positions and angles of the fingers and the thumb relative to each other and to the palm.
11. The method of claim 9, wherein the control object is a tool and the physical characteristics of the tool include at least one of:
length of the tool;
width of the tool; and
pointing direction vector of the tool.
10. The method of claim 8, wherein the control object is a tool and the physical characteristics of the tool include at least one of:
length of the tool;
width of the tool; and
pointing direction vector of the tool.
12. The method of claim 1, wherein the control object is a hand and identified construct portions include at least one fingers, carpals, knuckles, palm, and wrist.
11. The method of claim 1, wherein the control object is a hand and identified construct portions include at least one fingers, carpals, knuckles, palm, and wrist.
13. The method of claim 1, further including improving a 3D solid model's representation of the gestural motion by:
detecting conflicting attributes between adjacent 3D solid subcomponents; and
fitting, to the construct, 3D solid subcomponents with least conflicting attributes.
12. The method of claim 1, further including improving a 3D solid model's representation of the gestural motion by:
detecting conflicting attributes between adjacent 3D solid subcomponents based on the defined span and the defined span length; and
fitting, to the construct, 3D solid subcomponents with least conflicting attributes.
14. The method of claim 13, further including:
ranking the 3D solid subcomponents with conflicting attributes based on a degree of conflict; and
presenting the ranked 3D solid subcomponents for selection.
13. The method of claim 12, further including:
ranking the 3D solid subcomponents with conflicting attributes based on a degree of conflict; and
presenting the ranked 3D solid subcomponents for selection.
15. The method of claim 1, wherein the first unmatched contour point is arbitrarily identified.
14. The method of claim 1, wherein the first unmatched contour point is arbitrarily identified.
16. The method of claim 1, wherein the line is a convex curve line.
15. The method of claim 1, wherein the line is a convex curve line.
17. The method of claim 1, wherein the normal for the first unmatched point is determined by:
identifying a set of points proximate to the first unmatched point, wherein at least two points included in the set of points are not co-linear; and
determining the normal by obtaining a cross product of the set of points.
17. The method of claim 1, wherein the normal for the first unmatched contour point is determined by:
identifying a set of contour points proximate to the first unmatched contour point, wherein at least two contour points included in the set of contour points are not co-linear; and
determining the normal by obtaining a cross product of the set of points.
18. The method of claim 1, wherein the normal for the first unmatched point is determined by:
identifying a set of points proximate to the first unmatched point;
defining a first vector by subtracting a first point in the set of points from a second point in the set of points;
applying a rotation matrix to rotate the first vector by 90 decrees away from a center of mass of the set of points; and
determining the rotated first vector to be the normal.
18. The method of claim 1, wherein the normal for the first unmatched contour point is determined by:
identifying a set of contour points proximate to the first unmatched contour point;
defining a first vector by subtracting a first contour point in the set of contour points from a second contour point in the set of contour points;
applying a rotation matrix to rotate the first vector by 90 degrees away from a center of mass of the set of contour points; and
determining the rotated first vector to be the normal.
19. A non-transitory computer readable storage medium impressed with computer program instructions to accurately capture gestural motion of a control object in a three- dimensional (3D) sensory space, which computer program instructions, when executed on a processor, implement a method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determining of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
19. A non-transitory computer readable storage medium impressed with computer program instructions to accurately capture gestural motion of a control object in a three-dimensional (3D) sensory space, which computer program instructions, when executed on a processor, implement a method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time t0, the determining of the observation information including:
identifying a contour of the control object, the identified contour having a plurality of contour points;
identifying a first unmatched contour point of the plurality of contour points;
determining a normal for the first unmatched contour point;
identifying a second unmatched contour point of the plurality of contour points by locating an unmatched contour point that is closest to the first unmatched contour point and is reachable by a line having a most opposite normal to the normal for the first unmatched contour point;
defining a span as a shortest distance between the first unmatched contour point and the second unmatched contour point;
defining a span length as a length of the defined span; and
determining the observation information to include the defined span and the defined span length;
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time t0; and
responsive to modifications in the observation information based on another image captured at time t1, wherein the control object moved between t0 and t1, improving conformance of the 3D solid model to the modifications in the observation information.
20. A system to accurately capture gestural motion of a control object in a three- dimensional (3D) sensory space, comprising:
a processor and a computer readable storage medium storing computer instructions configured to cause the processor to:
determine observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determination of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
construct a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
20. A system to accurately capture gestural motion of a control object in a three-dimensional (3D) sensory space, comprising:
a processor and a computer readable storage medium storing computer instructions configured to cause the processor to:
determine observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time t0, the determining of the observation information including:
identify a contour of the control object, the identified contour having a plurality of contour points;
identify a first unmatched contour point of the plurality of contour points;
determine a normal for the first unmatched contour point;
identify a second unmatched contour point of the plurality of contour points by locating an unmatched contour point that is closest to the first unmatched contour point and is reachable by a line having a most opposite normal to the normal for the first unmatched contour point;
define a span as a shortest distance between the first unmatched contour point and the second unmatched contour point;
define a span length as a length of the defined span; and
determine the observation information to include the defined span and the defined span length;
construct a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time t0; and
responsive to modifications in the observation information based on another image captured at time t1, wherein the control object moved between t0 and t1, improve conformance of the 3D solid model to the modifications in the observation information.
Table 1
The table (Table 1) above shows that independent claims 1,19,20 of this Application is not identical to the claims of U.S. Patent No. 11,461,966. However, the claims are not patentably distinct. The U.S. Patent No. 11,461,966 is narrower than independent claims 1, 19,20 since it includes several additional limitations not found in claim 1,19,20 of the instant Application.
Claims 1–20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1–20 of U.S. Patent No. 12,236,528 B2.
Regarding Claims 1–20: The following table illustrates the correspondence between the claimed limitation of 1–20 of the current application and the claimed limitation of 1–20 of 12,236,528 Patent.
18,486,276 (instant app)
12,236,528 (U.S. Patent)
1. A method of accurately capturing gestural motion of a control object in a three- dimensional (3D) sensory space, the method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determining of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
2. The method of claim 1, further including:
responsive to modifications in the observation information based on another image captured at time tl, wherein the control object moved between tO and tl, improving conformance of the 3D solid model to the modifications in the observation information.
1. A method of accurately capturing gestural motion of a control object in a three-dimensional (3D) sensory space, the method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time t0, the determining of the observation information including:
determining a normal for a first unmatched contour point from among a plurality of contour points identified with the control object;
identifying a second unmatched contour point from among the plurality of contour points by locating an unmatched contour point that is closest to the first unmatched contour point and is reachable by a line having a most opposite normal to the normal for the first unmatched contour point; and
including a shortest distance between the first unmatched contour point and the second unmatched contour point in the observation information;
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time t0; and
responsive to modifications in the observation information based on another image captured at time t1, wherein the control object moved between t0 and t1, improving conformance of the 3D solid model to the modifications in the observation information.
3. The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of closed curves to at least a portion of a construct of the control object.
2. The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of closed curves to at least a portion of a construct of the control object.
4. The method of claim 3, wherein the set of closed curves includes at least one of radial solids, capsuloids, spheres, ellipsoids, and hyperboloids.
3. The method of claim 2, wherein the set of closed curves includes at least one of radial solids, capsuloids, spheres, ellipsoids, and hyperboloids.
5. The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of capsuloids to at least a portion of construct of the control object.
4. The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of capsuloids to at least a portion of construct of the control object.
6. The method of claim 1, wherein the control object is a hand and the fitting the one or more 3D solid subcomponents further includes at least one of:
fitting capsuloids to finger portions of a construct of the control object; and
fitting radial solids to palm and/or wrist portions of the construct.
5. The method of claim 1, wherein the control object is a hand and the fitting the one or more 3D solid subcomponents further includes at least one of:
fitting capsuloids to finger portions of a construct of the control object; and
fitting radial solids to palm and/or wrist portions of the construct.
7. The method of claim 1, wherein the improving of the conformance of the 3D solid model includes altering the 3D solid subcomponents to conform to at least one of length, width, orientation, and arrangement of portions of a construct of the control object.
6. The method of claim 1, wherein the improving of the conformance of the 3D solid model includes altering the 3D solid subcomponents to conform to at least one of length, width, orientation, and arrangement of portions of a construct of the control object.
8. The method of claim 7, wherein the altering of the 3D solid subcomponents further includes applying a transformation matrix to a plurality of points on the 3D solid subcomponents.
7. The method of claim 6, wherein the altering of the 3D solid subcomponents further includes applying a transformation matrix to a plurality of points on the 3D solid subcomponents.
9. The method of claim 1, wherein the constructing of the 3D solid model further includes determining the 3D solid subcomponents from physical characteristics of a type of control object being observed.
8. The method of claim 1, wherein the constructing of the 3D solid model further includes determining the 3D solid subcomponents from physical characteristics of a type of control object being observed.
10. The method of claim 9, wherein the control object is a hand and the physical characteristics of the hand include at least one of:
four fingers and a thumb of the hand;
a palm to which the fingers and the thumb are connected; and
positions and angles of the fingers and the thumb relative to each other and to the palm.
9. The method of claim 8, wherein the control object is a hand and the physical characteristics of the hand include at least one of:
four fingers and a thumb of the hand;
a palm to which the fingers and the thumb are connected; and
positions and angles of the fingers and the thumb relative to each other and to the palm.
11. The method of claim 9, wherein the control object is a tool and the physical characteristics of the tool include at least one of:
length of the tool;
width of the tool; and
pointing direction vector of the tool.
10. The method of claim 8, wherein the control object is a tool and the physical characteristics of the tool include at least one of:
length of the tool;
width of the tool; and
pointing direction vector of the tool.
12. The method of claim 1, wherein the control object is a hand and identified construct portions include at least one fingers, carpals, knuckles, palm, and wrist.
11. The method of claim 1, wherein the control object is a hand and identified construct portions include at least one fingers, carpals, knuckles, palm, and wrist.
13. The method of claim 1, further including improving a 3D solid model's representation of the gestural motion by:
detecting conflicting attributes between adjacent 3D solid subcomponents; and
fitting, to the construct, 3D solid subcomponents with least conflicting attributes.
12. The method of claim 1, further including improving a 3D solid model's representation of the gestural motion by:
detecting conflicting attributes between adjacent 3D solid subcomponents; and
fitting, to the construct, 3D solid subcomponents with least conflicting attributes.
14. The method of claim 13, further including:
ranking the 3D solid subcomponents with conflicting attributes based on a degree of conflict; and
presenting the ranked 3D solid subcomponents for selection.
13. The method of claim 12, further including:
ranking the 3D solid subcomponents with conflicting attributes based on a degree of conflict; and
presenting the ranked 3D solid subcomponents for selection.
15. The method of claim 1, wherein the first unmatched contour point is arbitrarily identified.
14. The method of claim 1, wherein the first unmatched contour point is arbitrarily identified.
16. The method of claim 1, wherein the line is a convex curve line.
15. The method of claim 1, wherein the line is a convex curve line.
17. The method of claim 1, wherein the normal for the first unmatched point is determined by:
identifying a set of points proximate to the first unmatched point, wherein at least two points included in the set of points are not co-linear; and
determining the normal by obtaining a cross product of the set of points.
17. The method of claim 1, wherein the normal for the first unmatched contour point is determined by:
identifying a set of contour points proximate to the first unmatched contour point, wherein at least two contour points included in the set of contour points are not co-linear; and
determining the normal by obtaining a cross product of the set of points.
18. The method of claim 1, wherein the normal for the first unmatched point is determined by:
identifying a set of points proximate to the first unmatched point;
defining a first vector by subtracting a first point in the set of points from a second point in the set of points;
applying a rotation matrix to rotate the first vector by 90 decrees away from a center of mass of the set of points; and
determining the rotated first vector to be the normal.
18. The method of claim 1, wherein the normal for the first unmatched contour point is determined by:
identifying a set of contour points proximate to the first unmatched contour point;
defining a first vector by subtracting a first contour point in the set of contour points from a second contour point in the set of contour points;
applying a rotation matrix to rotate the first vector by 90 degrees away from a center of mass of the set of contour points; and determining the rotated first vector to be the normal.
19. A non-transitory computer readable storage medium impressed with computer program instructions to accurately capture gestural motion of a control object in a three- dimensional (3D) sensory space, which computer program instructions, when executed on a processor, implement a method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determining of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
19. A non-transitory computer readable storage medium impressed with computer program instructions to accurately capture gestural motion of a control object in a three-dimensional (3D) sensory space, which computer program instructions, when executed on a processor, implement a method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time t0, the determining of the observation information including:
determining a normal for a first unmatched contour point from among a plurality of contour points identified with the control object;
identifying a second unmatched contour point from among the plurality of contour points by locating an unmatched contour point that is closest to the first unmatched contour point and is reachable by a line having a most opposite normal to the normal for the first unmatched contour point; and
including a shortest distance between the first unmatched contour point and the second unmatched contour point in the observation information;
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time t0; and
responsive to modifications in the observation information based on another image captured at time t1, wherein the control object moved between t0 and t1, improving conformance of the 3D solid model to the modifications in the observation information.
20. A system to accurately capture gestural motion of a control object in a three- dimensional (3D) sensory space, comprising:
a processor and a computer readable storage medium storing computer instructions configured to cause the processor to:
determine observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determination of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
construct a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
20. A system to accurately capture gestural motion of a control object in a three-dimensional (3D) sensory space, comprising:
a processor and a computer readable storage medium storing computer instructions configured to cause the processor to:
determine observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time t0, the determination of the observation information including:
determining a normal for a first unmatched contour point from among a plurality of contour points identified with the control object;
identifying a second unmatched contour point from among the plurality of contour points by locating an unmatched contour point that is closest to the first unmatched contour point and is reachable by a line having a most opposite normal to the normal for the first unmatched contour point; and
including a shortest distance between the first unmatched contour point and the second unmatched contour point in the observation information;
construct a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time t0; and
responsive to modifications in the observation information based on another image captured at time t1, wherein the control object moved between t0 and t1, improve conformance of the 3D solid model to the modifications in the observation information.
Table 1
The table (Table 1) above shows that independent claims 1,19,20 of this Application is not identical to the claims of U.S. Patent No. 12,236,528. However, the claims are not patentably distinct. The U.S. Patent No. 12,236,528 is narrower than independent claims 1,19,20 since it includes several additional limitations not found in claim 1,19,20 of the instant Application.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Perez et al. (US 2015/0153835 A1 plus US 9,645,654 B2) with Related U.S. Application Data Provisional application No. 61/911,975, filed on Dec. 4, 2013.
The applied reference has a common inventor with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(2). This rejection under 35 U.S.C. 102(a)(2) might be overcome by: (1) a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application and is thus not prior art in accordance with 35 U.S.C. 102(b)(2)(A); (2) a showing under 37 CFR 1.130(b) of a prior public disclosure under 35 U.S.C. 102(b)(2)(B) if the same invention is not being claimed; or (3) a statement pursuant to 35 U.S.C. 102(b)(2)(C) establishing that, not later than the effective filing date of the claimed invention, the subject matter disclosed in the reference and the claimed invention were either owned by the same person or subject to an obligation of assignment to the same person or subject to a joint research agreement.
Re 1., Perez discloses via said 61/911,975 A method of accurately capturing gestural motion of a control object in a three- dimensional (3D) sensory space, the method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO (or likewise “ [0050] In an embodiment, observation information including observation of the control object can be compared against the model at one or more of periodically, randomly or substantially continuously (i.e., in real time).”) , the determining of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object (or likewise “ A wide variety of techniques for determining a normal can be used in embodiments, but in one exemplary embodiment illustrated by the flowchart 132a of Fig. 1B-1-1, in a block 151, a set of points proximate to the first unmatched point, at least two of which are not co-linear, is determined.” [0027] penult S) ;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point (or likewise “ [0029] Again with reference to Fig. 1B-1, in block 133 of Fig. 1B-1, the closest second unmatched point B 204 (of block 24 of Fig. 2A) reachable by a convex curve (line 206) having the most opposite normal B1 205 is found.”); and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information (or likewise “In a representative embodiment illustrated by flowchart 122a, in block 135, a span can be found by determining a shortest convex curve for the point pairings A and B.” [0030] 3rd S); and
constructing a 3D solid model to represent the control object1 by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO (or likewise “In a block 182, portion(s) of object(s) as detected or captured are analyzed to determine fit to model portion(s) (see e.g., Figs. IG, IG-1, IG-2).” [0040] 3rd S via figs. 1G-1 & 1G-2:
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Re 2. , Perez discloses The method of claim 1, further including:
responsive to modifications in the observation information based on another image captured at time tl (or likewise “The more friction a model subcomponent has in the model, the less the subcomponent moves in response to new observed information.” [0066] 2nd S) 2 improving conformance of the 3D solid model to the modifications in the observation information (or likewise “ Variation detector 197G and model refiner 197F are further enabled to correlate among model portions to preserve continuity with characteristic information of a corresponding object being modeled, continuity in motion, and/or continuity in deformation, conformation and/or torsional rotations.” [0060], last S).
Re 3., Perez discloses The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of closed curves to at least a portion of a construct of the control object (or likewise “In a block 182, portion(s) of object(s) as detected or captured are analyzed to determine fit to model portion(s) (see e.g., Figs. IG, IG-1, IG-2).” [0040] 3rd S via figs. 1G-1 & 1G-2: closed curves:
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).
Re 4., Perez discloses The method of claim 3,
Re 5., Perez discloses The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of capsuloids (via said via figs. 1G-1 & 1G-2) to at least a portion of construct of the control object.
Re 6., Perez discloses The method of claim 1,
Re 7., Perez discloses The method of claim 13, wherein the improving of the conformance of the 3D solid model includes 4 arrangement of portions of a construct of the control object (or likewise “ [0060] The model subcomponents 197-1, 197-2, 197-3, and 197-4 can be scaled, sized, selected, rotated, translated, moved, or otherwise re-ordered to enable portions of the model corresponding to the virtual surface(s) to conform within the points 193 in space.”).
Re 8., Perez discloses The method of claim 7, wherein the altering of the 3D solid subcomponents further includes applying a transformation matrix to a plurality of points on the 3D solid subcomponents5.
Re 9., Perez discloses The method of claim 1, wherein the constructing of the 3D solid model further includes determining the 3D solid subcomponents from physical characteristics of a type of control object being observed (or likewise “ In an embodiment, the
model subcomponents 197-2, 197-3 can be selected from a set of radial solids, which can reflect at least a portion of a control object 99 in terms of one or more of structure, motion characteristics, conformational characteristics, other types of characteristics of control object 99, and/or combinations thereof.” [0048] 2nd S).
Re 10., Perez discloses The method of claim 9, wherein the control object is a hand (via said figs. 1G-1 & 1G-2) and the physical characteristics of the hand include at least one of:
four fingers and a thumb of the hand (via said figs. 1G-1 & 1G-2);
Re 11., Perez discloses The method of claim 9, wherein the control object is a tool (or likewise “Further, when the context is determined to be a styli (or other tool) held in the fingers of the user, the tool tip will be determined to be object of interest and a control object whereas the user's fingertips might be determined not to be objects
of interest (i.e., background).” [0070] 4th S) and the physical characteristics of the tool include at least one of:
length of the tool (or likewise “pencil6…tool” [0025] penult S);
width of the tool (or likewise “pencil7…tool” [0025] penult S)
Re 12., Perez discloses The method of claim 1,
Re 13., Perez discloses The method of claim 1, further including improving a 3D solid model's representation of the gestural motion by:
detecting conflicting attributes between adjacent 3D solid subcomponents; and
fittingcapsoloids, each having one or more attributes ( e.g., determined minima and/or maxima of intersection angles between capsoloids) can be determined. In an embodiment, determining a relationship between a first capsoloid having a first set of attributes and a second capsoloid having a second set of attributes includes detecting and resolving conflicts between first attribute and second attributes.” [0063] 3rd & 4th Ss).
Re 14., Perez discloses The method of claim 13, further including:
ranking the 3D solid subcomponents with conflicting attributes based on a degree of conflict; and
presenting the ranked 3D solid subcomponents for selection (or likewise:
“[0060] The model subcomponents 197-1, 197-2, 197-3, and 197-4 can be scaled, sized, selected, rotated, translated, moved, or otherwise re-ordered to enable portions of the model corresponding to the virtual surface(s) to conform within the points 193 in space.”).
Re 15., Perez discloses The method of claim 1,
Re 16., Perez discloses The method of claim 1
Re 17., Perez discloses The method of claim 1,
8.
Re 18., Perez discloses The method of claim 1,
9.
Claim 19 rejected like claim 1:
Re 19., Perez discloses A non-transitory computer readable storage medium impressed with computer program instructions to accurately capture gestural motion of a control object in a three- dimensional (3D) sensory space, which computer program instructions, when executed on a processor, implement a method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determining of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
Claim 20 rejected like claims 1 and 19:
Re 20., Perez discloses A system to accurately capture gestural motion of a control object in a three- dimensional (3D) sensory space, comprising:
a processor and a computer readable storage medium storing computer instructions configured to cause the processor to:
determine observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determination of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
construct a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 9,785,247 B1) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2018/0032144 A1 plus corresponding US 9,983,686 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2019/0033975 A1 plus corresponding US 10,429,943 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2020/0033951 A1 plus corresponding US 10,936,082 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2021/0181859 A1 plus corresponding US 11,586,292 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2023/0205321 A1 plus corresponding US 11,914,792 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2024/0201794 A1 plus corresponding US 12,314,478 B2) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by HOROWITZ et al. (US 2025/0390178 A1) with Related U.S. Application Data Provisional application No. 61/996,778, filed on May 14, 2014.
The above applied reference(s) has a common inventor with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(2). This rejection under 35 U.S.C. 102(a)(2) might be overcome by: (1) a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application and is thus not prior art in accordance with 35 U.S.C. 102(b)(2)(A); (2) a showing under 37 CFR 1.130(b) of a prior public disclosure under 35 U.S.C. 102(b)(2)(B) if the same invention is not being claimed; or (3) a statement pursuant to 35 U.S.C. 102(b)(2)(C) establishing that, not later than the effective filing date of the claimed invention, the subject matter disclosed in the reference and the claimed invention were either owned by the same person or subject to an obligation of assignment to the same person or subject to a joint research agreement.
Re 1., HOROWITZ discloses via said 61/996,778 A method of accurately capturing gestural motion of a control object in a three- dimensional (3D) sensory space, the method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determining of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
constructing a 3D solid model to represent the control object10 by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO (or likewise “[00153] In some implementations, each of a number of slices is analyzed separately to determine the size and location of an elliptical cross-section of the object in that slice. This provides an initial 3D model (specifically, a stack of elliptical cross-sections), which
can be refined by correlating the cross-sections across different slices.” As shown in fig. 12C:
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Re 2., HOROWITZ discloses The method of claim 1, further including:
responsive to modifications in the observation information based on another image captured at time tl11 improving conformance of the 3D solid model to the modifications in the observation information (or likewise: [0080) In an embodiment, when the control object morphs, conforms, and/or translates, motion information reflecting such motion(s) is included into the observed information. Points in space can be recomputed based on the new observation information. The model subcomponents can be scaled, sized, selected, rotated, translated, moved, or otherwise re-ordered to enable portions of the model corresponding to the virtual surface(s) to conform within the set of points in space.”).
Re 3., HOROWITZ discloses The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of closed curves to at least a portion of a construct of the control object (or likewise “[00153] In some implementations, each of a number of slices is analyzed separately to determine the size and location of an elliptical cross-section of the object in that slice. This provides an initial 3D model (specifically, a stack of elliptical cross-sections), which
can be refined by correlating the cross-sections across different slices.” As shown in fig.
12C:
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Re 4., HOROWITZ discloses The method of claim 3,
Re 5., HOROWITZ discloses The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of capsuloids (fig. 2A) to at least a portion of construct of the control object (fig. 2A:
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Re 6., HOROWITZ discloses The method of claim 1, wherein the control object is a hand (via said fig. 2A)
Re 7., HOROWITZ discloses The method of claim 1, wherein the improving (i.e., re-ordering/re-regulating: Dictionary.com) of the conformance of the 3D solid model includes altering the 3D solid subcomponents to conform to 12
Re 8., HOROWITZ discloses The method of claim 7,
Re 9., HOROWITZ discloses The method of claim 1, wherein the constructing of the 3D solid model further includes determining the 3D solid subcomponents from physical characteristics of a type of control object being observed (or likewise “ In
an embodiment, the model subcomponents can be selected from a set of radial solids,
which can reflect at least a portion of a control object 114 in terms of one or more of
structure, motion characteristics, conformational characteristics, other types of characteristics of control object 114, and/or combinations thereof.” [0077] 5th S) .
Re 10., HOROWITZ discloses The method of claim 9, wherein the control object is a hand (via said fig. 2A) and the physical characteristics of the hand include at least one of:
four fingers and a thumb of the hand (via said fig. 2A);
Re 11., HOROWITZ discloses The method of claim 9, wherein the control object is a tool (or likewise “[00126] In one implementation, a method of providing command input to a machine under control by tracking hands ( or other body portions, alone or in conjunction with tools) using a sensory machine control system includes capturing sensory information for a human body portion within a field of interest”) and the physical characteristics of the tool include at least one of:
pointing direction vector (or likewise a trajectory vector via “For example, gestures can be stored as vectors, i.e., mathematically specified spatial trajectories, and the gesture record can have a field specifying the relevant part of the user's body making the gesture; thus, similar trajectories executed by a user's hand and head can be stored in the database as different gestures so that an application can interpret them differently.” [0076]) of the tool.
Re 12., HOROWITZ discloses The method of claim 1, wherein the control object is a hand (via said fig. 2A)
Re 13., HOROWITZ discloses The method of claim 1, further including improving a 3D solid model's representation of the gestural motion by:
detecting conflicting attributes between adjacent 3D solid subcomponents; and
fitting
Re 14., HOROWITZ discloses The method of claim 13, further including:
ranking the 3D solid subcomponents with conflicting attributes based on a degree of conflict; and
presenting the ranked 3D solid subcomponents for selection (or likewise “The model subcomponents can be scaled, sized, selected, rotated,
translated, moved, or otherwise re-ordered to enable portions of the model corresponding
to the virtual surface(s) to conform within the set of points in space.” [0080] last S).
Re 15., HOROWITZ discloses The method of claim 1,
Re 16., HOROWITZ discloses The method of claim 1,
Re 17., HOTOWITZ discloses The method of claim 1,
13.
Re 18., HOROWITZ discloses The method of claim 1,
14.
Claim 19 rejected like claim 1:
Re 19., HOROWITZ discloses A non-transitory computer readable storage medium impressed with computer program instructions to accurately capture gestural motion of a control object in a three- dimensional (3D) sensory space, which computer program instructions, when executed on a processor, implement a method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determining of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
Claim 20 rejected like claims 1,19:
Re 20., HOROWITZ discloses A system to accurately capture gestural motion of a control object in a three- dimensional (3D) sensory space, comprising:
a processor and a computer readable storage medium storing computer instructions configured to cause the processor to:
determine observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determination of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
construct a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Matinez del Rincon (Feature-based human tracking: from coarse to fine)15:
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Re 1., Martinez teaches A method of accurately capturing gestural motion of a control object in a three- dimensional (3D) sensory space, the method including:
determining observation information characterizing gestural motion (or likewise “recognize gestures…for example…tracking a hand”, pg. 154, 6.1.4 Volumetric Models, last para, 1st S) of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determining of the observation information including (as shown by the hands in fig. 6.11:
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):
determining a normal for a first unmatched point from among a plurality of points identified with the control object (or likewise “fitting…perpendicular lines…for every model point”, pg. 161, Silhouette matching, 1st para, 2nd & 3rd Ss as shown in fig. 6.8:
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identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to1617 the first unmatched point (or said likewise “fitting…perpendicular lines…for every model point…by finding the closest allowable shape…x”, pg. 161, Silhouette matching, 1st para, 2nd & 3rd Ss & 2nd para 1st & 2nd Ss, wherein shape x “is a vector composed of n points”, pg. 159, Algorithm 10: Procrustes Analysis: in the beginning “Given a set of M contours X” statement) and is reachable18 by a line (active-moving snake contour) having a most opposite normal to19 the normal (or likewise an normal on the front and back or top and bottom via fig. 6.8) for the first unmatched point (via fig. 6.8:
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); and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information (or likewise “finding the closest20 allowable…shape x…vector b”, pg. 161, Silhouette matching, 2nd para, 1st & 2nd Ss, wherein shape x “is a vector composed of n points”, pg. 159, Algorithm 10: Procrustes Analysis: in the beginning “Given a set of M contours X” statement) ; and
constructing a 3D 21 (or likewise “Our main goal is to construct a mathematical model which represents a human body”, pg. 157, 6.2.1.1 Training,1st para, 1st S) by fitting one or more 3D 6.2.1 Active Shape Models, 1st para, 2nd S to 2nd para, 3rd S) defined by the observation information based on the image captured at time tO.
Re 2., Martinez discloses The method of claim 1, further including:
responsive to modifications in the observation information based on another image captured at time tl22 improving conformance23 of the 3D solid model to the modifications (or likewise “The fitting process is an iterative one, where the model uses suggested movement from control points to find natural resting place”, pg. 161, Silhouette matching, 1st para, 2nd S)) in the observation information.
Re 3., Martinez discloses The method of claim 1, wherein the fitting of the one or more 3D solid subcomponents further includes fitting a set of closed curves (or likewise said active contour of fig. 6.8) to at least a portion of a construct of the control object.
Re 4., Martinez discloses The method of claim 3,
Re 5., Martinez discloses The method of claim 1, 24
Re 6. , Martinez discloses The method of claim 1,
25 26 27
Re 728., Martinez discloses The method of claim 1, wherein the improving of the conformance of the 3D solid model includes altering the 3D solid subcomponents to conform to29 at least one of length, width30 (or likewise “As model fitting31…we find the position of the silhouette and skeleton points in a new image”, pg. 160, 6.2.1.3 Model fitting, 1st para, 1st S) of portions of a construct32 of the control object.
Re 8., Martinez discloses The method of claim 7, wherein the altering of the 3D solid subcomponents further includes applying a transformation matrix to33 a plurality (or likewise “using a transition34 matrix learned using the training dataset…This model fitting is applied following…the PTM” (Probabilistic Transition Matrix), pg. 177, 5th para, last S and pg, 179, 2nd para, penult S) of points on the 3D
Re 9., Martinez discloses The method of claim 1, wherein the constructing of the 3D solid model further includes determining the 3D 6.2.2.5 Image tracking, 1st para, 1st S) of a type of control object being observed.
Re 10., Martinez discloses The method of claim 9,
Re 11., Martinez discloses The method of claim 9,
Re 12., Martinez discloses The method of claim 1
Re 13., Martinez discloses The method of claim 1, further including improving a 3D
detecting conflicting attributes (or likewise “tracking35 of the articulated model… using information36 intrinsic to the ‘step’ of interest (see Figure 6.34)”, pg. 182, 6.3.1 Limb Tracking: General Principle, 3rd para, 3rd S, wherein “reduction of complexity is achieved by the detection of the pivot foot – i.e. the foot which is static during a step – and its trajectory during a whole step”, pg. 182, 6.3 Articulated Tracking, 2nd para, 4th S) between adjacent
Re 14., Martinez discloses The method of claim 13, further including:
ranking37 the 3D solid subcomponents with conflicting attributes based on a degree of (biomechanical-step-solving) conflict; and
presenting the ranked 3D solid subcomponents for selection (or likewise “we select in each iteration the closest allowable shape from the training set by means of a nearest neighbor classifier…as it can be noticed in Figure 6.13”, pg. 163, last para, 3rd & 4th Ss via fig. 6.13:
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968
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).
Re 15., Martinez discloses The method of claim 1,
Re 16., Martinez discloses The method of claim 1,
Re 17., Martinez discloses The method of claim 1,
38.
Re 18., Martinez discloses The method of claim 1
39.
Claim 19 rejected like claim 1:
Re 19., Martinez discloses A non-transitory computer readable storage medium40 (or likewise a computer “input human blob provided by the Rao-Blackwellised particle filter”, pg. 179, 2nd para, 2nd S and “output”, pg. 187, 6.3.3.2 Multiple particle filter tracking, 2nd para, 2nd S) impressed with computer program instructions to accurately capture gestural motion of a control object in a three- dimensional (3D) sensory space, which computer program instructions, when executed on a processor, implement a method including:
determining observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determining of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
constructing a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
Claim 20 rejected like claims 1 and 19:
Re 20., Martinez discloses A system to accurately capture gestural motion of a control object in a three- dimensional (3D) sensory space, comprising:
a processor and a computer readable storage medium storing computer instructions configured to cause the processor to:
determine observation information characterizing gestural motion of a control object in a three-dimensional (3D) sensory space from at least one image captured at time tO, the determination of the observation information including:
determining a normal for a first unmatched point from among a plurality of points identified with the control object;
identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point; and
including a shortest distance between the first unmatched point and the second unmatched point in the observation information; and
construct a 3D solid model to represent the control object by fitting one or more 3D solid subcomponents to a construct of the control object defined by the observation information based on the image captured at time tO.
Conclusion
The prior art “nearest to the subject matter defined in the claims” (MPEP 707.05) made of record and not relied upon is considered pertinent to applicant's disclosure.
The following table lists several references that are relevant to the subject matter claimed and disclosed in this Application. The references are not relied on by the Examiner, but are provided to assist the Applicant in responding to this Office action:
Citation
Relevance
IDS cited KIM et al (US 2014/0015831 A1)
KIM teaches P1/P2 “point”-“normal vectors” via [0014][0015] and fig. 4: 36a,36b:
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[0014] The manipulation processing unit may further include a contact point tracking unit configured to calculate a normal vector directed from the contact point with the surface of the 3D virtual object to a center of gravity of the 3D virtual object and to track the path of the contact point, from a time at which the contact determination unit determines that the manipulating object is in contact with the surface of the 3D virtual object.
[0015] The contact point tracking unit may, if the contact point includes two or more contact points, calculate normal vectors with respect to the two or more contact points, and tracks paths of the two or more contact points.
as the closest to the claimed “identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point” of claim 1.
Kramer et al. (US 7,472,047 B2)
Kramer teaches a “normal”- “offset vector” via c.16,ll.50-60 and fig. 13:
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“The output of the collision tracking algorithm is an offset vector lying in the direction of the normal to the surface tangent plane of object B and, when objects A and B are disjoint, gives the displacement vector necessary for object A to just touch object B. We denote this collision-tracking algorithm by the function c operating on two objects, A and B, as o.sub.An=c(A, B).”
as the closest to the claimed “identifying a second unmatched point from among the plurality of points by locating an unmatched point that is closest to the first unmatched point and is reachable by a line having a most opposite normal to the normal for the first unmatched point” of claim 1.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DENNIS ROSARIO whose telephone number is (571)272-7397. The examiner can normally be reached Monday-Friday, 9AM-5PM EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Henok Shiferaw can be reached at 571-272-4637. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DENNIS ROSARIO/Examiner, Art Unit 2676
/Henok Shiferaw/Supervisory Patent Examiner, Art Unit 2676
1 MEANING AND PURPOSE of claim 1: “to represent the control object”
2 MEANING AND PURPOSE: The crossed text is not a limitation in a claim [i.e., claims 2,4,6,10, 11,12,15,16,17,18]… where the clause gave ‘meaning and purpose to the manipulative steps’ “ via:
MPEP 2111.04 "Adapted to," "Adapted for," "Wherein," "Whereby," and Contingent Clauses [R-10.2019]
I. "ADAPTED TO," "ADAPTED FOR," "WHEREIN," and "WHEREBY"
Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure. However, examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are:
(A) "adapted to" or "adapted for" clauses;
(B) "wherein" clauses; and
(C) "whereby" clauses.
The determination of whether each of these clauses is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002) (finding that a "wherein" clause limited a process claim where the clause gave "meaning and purpose [i.e. MEANING AND PURPOSE of claim 1: “to represent the control object”] to the manipulative steps").
3 Claim 7 interpreted to depend on claim 2.
4 The crossed text is “a narrow subset of claim scope…that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim [i.e., claims 1,7,10,11] under the broadest reasonable claim interpretation” via MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024]
"All words in a claim must be considered in judging the patentability of that claim against the prior art." In re Wilson, 424 F.2d 1382, 1385, 165 USPQ 494, 496 (CCPA 1970).
Examiners must consider all claim limitations when determining patentability of an invention over the prior art. In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 403-04 (Fed. Cir. 1983). The subject matter of a properly construed claim is defined by the terms that limit the scope of the claim when given their broadest reasonable interpretation. In Axonics, Inc. v. Medtronic, Inc., 73 F.4th 950, 958-59, 2023 USPQ2d 795 (Fed. Cir. 2023), the court found the claims were improperly narrowed based on a preferred embodiment to sacral anatomy or sacral neuromodulation, whereas the patent claims made no reference to sacral anatomy or sacral neuromodulation. Thus, the relevant prior art was improperly limited to a narrow subset of claim scope. See also MPEP § 2111 et seq. It is the subject matter of the properly construed claim that must be examined. The determination of whether particular language is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002).
As a general matter, the grammar and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
5 Claim 8 is taught since one of the Markush alternatives in claim 7 is taught
6 pencil: a slender, pointed piece of a substance used for marking, wherein slender is defined: having a circumference that is small in proportion to the height or length. (Dictionary.com)
7 pencil: a slender, pointed piece of a substance used for marking, wherein slender is defined: having a circumference that is small in proportion to the height or length. (Dictionary.com)
8 Regarding the crossed text of claim 17, see MEANING AND PURPOSE footnote of claim 2
9 Regarding the crossed text of claim 18, see MEANING AND PURPOSE footnote of claim 2
10 MEANING AND PURPOSE of claim 1: “to represent the control object”
11 MEANING AND PURPOSE: The crossed text is not a limitation in a claim [i.e., claims 2,4,6,10,11,12,15,16,17,18]… where the clause gave ‘meaning and purpose to the manipulative steps’ “ via:
MPEP 2111.04 "Adapted to," "Adapted for," "Wherein," "Whereby," and Contingent Clauses [R-10.2019]
I. "ADAPTED TO," "ADAPTED FOR," "WHEREIN," and "WHEREBY"
Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure. However, examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are:
(A) "adapted to" or "adapted for" clauses;
(B) "wherein" clauses; and
(C) "whereby" clauses.
The determination of whether each of these clauses is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002) (finding that a "wherein" clause limited a process claim where the clause gave "meaning and purpose [i.e. MEANING AND PURPOSE of claim 1: “to represent the control object”] to the manipulative steps").
12 The crossed text is “a narrow subset of claim scope…that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim [i.e., claims 1,7,10,11] under the broadest reasonable claim interpretation” via MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024]
"All words in a claim must be considered in judging the patentability of that claim against the prior art." In re Wilson, 424 F.2d 1382, 1385, 165 USPQ 494, 496 (CCPA 1970).
Examiners must consider all claim limitations when determining patentability of an invention over the prior art. In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 403-04 (Fed. Cir. 1983). The subject matter of a properly construed claim is defined by the terms that limit the scope of the claim when given their broadest reasonable interpretation. In Axonics, Inc. v. Medtronic, Inc., 73 F.4th 950, 958-59, 2023 USPQ2d 795 (Fed. Cir. 2023), the court found the claims were improperly narrowed based on a preferred embodiment to sacral anatomy or sacral neuromodulation, whereas the patent claims made no reference to sacral anatomy or sacral neuromodulation. Thus, the relevant prior art was improperly limited to a narrow subset of claim scope. See also MPEP § 2111 et seq. It is the subject matter of the properly construed claim that must be examined. The determination of whether particular language is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002).
As a general matter, the grammar and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
13 Regarding the crossed text of claim 17, see above MEANING AND PURPOSE footnote of claim 2
14 Regarding the crossed text of claim 18, see above MEANING AND PURPOSE footnote of claim 2
15 A higher quality copy (49 pages) of chapter 6 of Matinez del Rincon (Feature-based human tracking: from coarse to fine) as mapped to the 35 USC 102(a)(1) rejection of claims 1-20 is provided
16 Regarding claim 1’s “to” with respect to applicant’s disclosure:
[00159] The terms (“to”) and expressions employed herein are used as terms and expressions of description and not of limitation, and there is no intention, in the use of such terms (“to”) and expressions, of excluding any equivalents of the features shown and described or portions thereof. In addition, having described certain implementations of the technology disclosed, it will be apparent to those of ordinary skill in the art that other implementations incorporating the concepts disclosed herein can be used without departing from the spirit and scope of the technology disclosed. Accordingly, the described implementations are to be considered in all respects as only illustrative and not restrictive.
17 to: (used for expressing addition or accompaniment) with. (Dictionary.com)
18 BROAD CLAIM LANGUAGE: reach: to get to or get as far as in moving, going, traveling, etc.. (Dictionary.com)
19 to: (used for expressing addition or accompaniment) with. (Dictionary.com)
20 close: having the parts or elements near to one another, wherein near is defined: at, within, or to a short distance. (Dictionary.com)
21 MEANING AND PURPOSE of claim 1: “to represent the control object”, wherein represent is defined: to be the equivalent of; correspond to. (Dictionary.com)
22 MEANING AND PURPOSE: The crossed text is not “a limitation in a claim [i.e., claims 2,4,6,10,11,12,15,16,17,18]… where the clause gave ‘meaning and purpose to the manipulative steps’ “ via:
MPEP 2111.04 "Adapted to," "Adapted for," "Wherein," "Whereby," and Contingent Clauses [R-10.2019]
I. "ADAPTED TO," "ADAPTED FOR," "WHEREIN," and "WHEREBY"
Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure. However, examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are:
(A) "adapted to" or "adapted for" clauses;
(B) "wherein" clauses; and
(C) "whereby" clauses.
The determination of whether each of these clauses is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002) (finding that a "wherein" clause limited a process claim where the clause gave "meaning and purpose [i.e. MEANING AND PURPOSE of claim 1: “to represent the control object”] to the manipulative steps").
23 conform: to be in accordance; fit in (Dictionary.com)
24 -oid: A suffix meaning “like” or “resembling,” as in ellipsoid, a geometric solid that resembles an ellipse. (Dictioanry.com)
25 -oid: A suffix meaning “like” or “resembling,” as in ellipsoid, a geometric solid that resembles an ellipse, wherein resemble is defined: to be like or similar to (Dictionary.com)
26 construct: something constructed. (Dictionary.com)
27 of: (used to indicate possession, connection, or association). (Dictionary.com)
28 Claim 7 is interpreted to depend on claim 2’s “improving conformance”.
29 to: (used for expressing addition or accompaniment) with. (Dictionary.com)
30 The crossed text is “a narrow subset of claim scope…that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim [i.e., claims 1,7,10,11] under the broadest reasonable claim interpretation” via MPEP 2143.03 All Claim Limitations Must Be Considered [R-01.2024]
"All words in a claim must be considered in judging the patentability of that claim against the prior art." In re Wilson, 424 F.2d 1382, 1385, 165 USPQ 494, 496 (CCPA 1970).
Examiners must consider all claim limitations when determining patentability of an invention over the prior art. In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 403-04 (Fed. Cir. 1983). The subject matter of a properly construed claim is defined by the terms that limit the scope of the claim when given their broadest reasonable interpretation. In Axonics, Inc. v. Medtronic, Inc., 73 F.4th 950, 958-59, 2023 USPQ2d 795 (Fed. Cir. 2023), the court found the claims were improperly narrowed based on a preferred embodiment to sacral anatomy or sacral neuromodulation, whereas the patent claims made no reference to sacral anatomy or sacral neuromodulation. Thus, the relevant prior art was improperly limited to a narrow subset of claim scope. See also MPEP § 2111 et seq. It is the subject matter of the properly construed claim that must be examined. The determination of whether particular language is a limitation in a claim depends on the specific facts of the case. See, e.g., Griffin v. Bertina, 285 F.3d 1029, 1034, 62 USPQ2d 1431 (Fed. Cir. 2002).
As a general matter, the grammar and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
31 fit: to be of the right size or shape, as a garment for the wearer or any object or part for a thing to which it is applied. (Dictionary.com)
32 construct: something constructed. (Dictionary.com)
33 (used for expressing addition or accompaniment) with. (Dictionary.com)
34 transition: movement, passage, or change from one position, state, stage, subject, concept, etc., to another; change, wherein change is defined: to become transformed or converted (usually followed byinto ). (Dictionary.com)
35 track: to observe or monitor the course or path of (an aircraft, rocket, satellite, star, etc.), as by radar or radio signals., wherein monitor is defined: to observe, record, or detect (an operation or condition) with instruments that have no effect upon the operation or condition. (Dictionary.com)
36 information: Computers. important or useful facts obtained as output from a computer by means of processing input data with a program, wherein fact is defined: that which actually exists or is the case; reality or truth, wherein truth is defined: the state or character of being true. (Dictionary.com)
37 BROAD CLAIM LANGUAGE: rank: to assign to a particular position, station, class, etc.. (Dictionary.com)
38 Regarding the crossed text of claim 17, see MEANING AND PURPOSE footnote of claim 2
39 Regarding the crossed text of claim 18, see MEANING AND PURPOSE footnote of claim 2
40 Applicant’s disclosure:
[00122] Computer programs incorporating various features of the technology disclosed can be encoded on various computer readable storage media; suitable media include magnetic disk or tape, optical storage media such as compact disk (CD) or DVD (digital versatile disk), flash memory, and any other non-transitory medium capable of holding data in a computer-readable form. Computer readable storage media encoded with the program code can be packaged with a compatible device or provided separately from other devices. In addition program code can be encoded and transmitted via wired optical, and/or wireless networks conforming to a variety of protocols, including the Internet, thereby allowing distribution, e.g., via Internet download.
[00145] This method and other implementations of the technology disclosed can include one or more of the following features and/or features described in connection with additional methods disclosed. Other implementations can include a non-transitory computer readable storage medium storing instructions executable by a processor to perform any of the methods described above. Yet another implementation can include a system including memory and one or more processors operable to execute instructions, stored in the memory, to perform any of the methods described above.
[00158] This method and other implementations of the technology disclosed can include one or more of the following features and/or features described in connection with additional methods disclosed. Other implementations can include a non-transitory computer readable storage medium storing instructions executable by a processor to perform any of the methods described above. Yet another implementation can include a system including memory and one or more processors operable to execute instructions, stored in the memory, to perform any of the methods described above.
Prosecution Insights