DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Specification
Abstract
The abstract of the disclosure is objected to because it isn’t relevant to the current set of claims. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Title of the Invention
The title of the invention is not descriptive, and isn’t relevant to the current set of claims. A new title is required that is clearly indicative of the invention to which the claims are directed.
The following title is suggested:
METHOD AND MACHINE-READABLE MEDIUM FOR GENERATING AN ENVIRONMENT MAP FROM AN UPDATED SERVER-SIDE POINT CLOUD OR MOBILE STATION-SIDE POINT CLOUD.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 and 20 (see the last limitations), recite: “generating, by the computer system, at least a portion of an environment map from the updated server-side point cloud or the mobile station-side point cloud,” however it is not clear if the claim is referring to the mobile station-side point cloud or the updated mobile station-side point cloud. Therefore claims 1 and 20 are indefinite.
Claim 1 is presented below for reference.
1. A tangible, non-transitory, machine-readable medium storing instructions that when
executed by one or more processors effectuate operations comprising:
obtaining, by a computer system, a server-side point cloud generated by a server;
obtaining, by the computer system, a mobile station-side point cloud generated by a
mobile device;
combining, by the computer system, at least one of the mobile station-side point cloud
with data from the server-side point cloud to form an updated mobile station-side point
cloud or the server-side point cloud with data from the mobile station-side point cloud to
form an updated server-side point cloud; and
generating, by the computer system, at least a portion of an environment map from
the updated server-side point cloud or the mobile station-side point cloud.
Claims 2-19 depend from claim 1 and are therefore rejected by the same rationale as claim 1.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 15 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Claim 15 recites: “15. The medium of claim 1, wherein the operations further comprise steps for generating the mobile station-side point cloud.” However, claim 1 already mentions a mobile station-side point cloud being generated.
Claim 1 is presented below for reference.
1. A tangible, non-transitory, machine-readable medium storing instructions that when
executed by one or more processors effectuate operations comprising:
obtaining, by a computer system, a server-side point cloud generated by a server;
obtaining, by the computer system, a mobile station-side point cloud generated by a
mobile device;
combining, by the computer system, at least one of the mobile station-side point cloud
with data from the server-side point cloud to form an updated mobile station-side point
cloud or the server-side point cloud with data from the mobile station-side point cloud to
form an updated server-side point cloud; and
generating, by the computer system, at least a portion of an environment map from
the updated server-side point cloud or the mobile station-side point cloud.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Double Patenting
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
A statutory type (35 U.S.C. 101) double patenting rejection can be overcome by canceling or amending the claims that are directed to the same invention so they are no longer coextensive in scope. The filing of a terminal disclaimer cannot overcome a double patenting rejection based upon 35 U.S.C. 101.
Claims 1-20 is/are rejected under 35 U.S.C. 101 as claiming the same invention as that of claims 1-20 of prior U.S. Patent No. 12,154,332. This is a statutory double patenting rejection.
Claims of 18,929,194 Claims of US12,154,332
1. A tangible, non-transitory, machine-readable medium storing instructions that when executed by one or more processors effectuate operations comprising:
obtaining, by a computer system, a server-side point cloud generated by a server;
obtaining, by the computer system, a mobile station-side point cloud generated by a mobile device;
combining, by the computer system, at least one of the mobile station-side point cloud with data from the server-side point cloud to form an updated mobile station-side point cloud or the server-side point cloud with data from the mobile station-side point cloud to form an updated server-side point cloud; and
generating, by the computer system, at least a portion of an environment map from the updated server-side point cloud or the mobile station-side point cloud.
2. The medium of claim 1, wherein the operations further comprise:
creating, by the computer system at the server, the server-side point cloud using an image of a camera of the mobile device, motion data of the mobile device, and orientation data of the camera that is associated with the image.
3. The medium of claim 2, wherein the motion data includes inertial measurement data from an inertial measurement unit of the mobile device and the orientation data includes pose-transform data.
4. The medium of claim 2, wherein point coordinates of points of the mobile station-side point cloud are changed with aid of the motion data or the orientation data evaluated by the server, in particular in that a drift of the point coordinates of the points on the mobile station-side point cloud is corrected.
5. The medium of claim 2, wherein the orientation data is corrected on by the server with aid of the motion data.
6. The medium of claim 2, wherein at least one of a feature recognition or a feature description is performed by the server in the image using multi-scale oriented patches (MOPS) or scale-invariant feature transform (SIFT).
7. The medium of claim 2, wherein features are learned on by the server during at least one of feature recognition or a feature description that use deep learning.
8. The medium of claim 2, wherein a bundle adjustment is performed on by the server in the image.
9. The medium of claim 2, wherein the operations further comprise:
determining, based on a server evaluation of the image, setting data for the camera; and
transmitting the setting data to the mobile device.
10. The medium of claim 1, wherein the server-side point cloud or the mobile station-side point cloud is generated using a simultaneous localization and mapping algorithm.
11. The medium of claim 1, wherein the server-side point cloud and the mobile station-side point cloud include respective point coordinates, points of the server-side point cloud and the mobile station-side point cloud correspond respectively to a point coordinate.
12. The medium of claim 11, wherein the point coordinates are represented by vectors.
13. The medium of claim 1, wherein during the combination of the server-side point cloud with the mobile station-side point cloud, at least one of the following is performed: points of the server-side point cloud are at least partially supplemented by points of the mobile station-side point cloud, point coordinates of the points of the server-side point cloud are at least partially converted with aid of point coordinates of the points of the mobile station-side point cloud, at least one of the points of the mobile station-side point cloud are at least partially supplemented by the points of the server-side point cloud, the point coordinates of the points of the mobile station-side point cloud are at least partially converted with aid of the point coordinates of the points of the server-side point cloud.
14. The medium of claim 1, wherein the operations further comprise:
removing, using statistical evaluation, an outlier from the mobile station-side point cloud.
15. The medium of claim 1, wherein the operations further comprise steps for generating the mobile station-side point cloud.
16. The medium of claim 1, wherein the operations further comprise:
determining, using the server-side point cloud, a loop closure; and
correcting, using the loop closure, a drift of points of the mobile station-side point cloud.
17. The medium of claim 16, wherein the correcting the drift includes a linear adjustment
18. The medium of claim 1, wherein the operations further comprise:
operating, by the computer system, an augmented reality application using the server-side point cloud or the mobile station-side point cloud.
19. The medium of claim 1, wherein the operations further comprise:
determining at least two instances for the server-side point cloud, wherein in each instance at least one feature is learned by at least one of a feature recognition or a feature description by the server and the respective instances together with features are transmitted to the mobile device.
20. A method, comprising:
obtaining, by a computer system, a server-side point cloud generated by a server;
obtaining, by the computer system, a mobile station-side point cloud generated by a mobile device;
combining, by the computer system, at least one of the mobile station-side point cloud with data from the server-side point cloud to form an updated mobile station-side point cloud or the server-side point cloud with data from the mobile station-side point cloud to form an updated server-side point cloud; and
generating, by the computer system, at least a portion of an environment map from the updated server-side point cloud or the mobile station-side point cloud.
1. A tangible, non-transitory, machine-readable medium storing instructions that when executed by one or more processors effectuate operations comprising:
obtaining, by a computer system, a server-side point cloud generated by a server;
obtaining, by the computer system, a mobile station-side point cloud generated by a mobile device;
combining, by the computer system, at least one of the mobile station-side point cloud with data from the server-side point cloud to form an updated mobile station-side point cloud or the server-side point cloud with data from the mobile station-side point cloud to form an updated server-side point cloud; and
generating, by the computer system, at least a portion of an environment map from the updated server-side point cloud or the mobile station-side point cloud.
2. The medium of claim 1, wherein the operations further comprise:
creating, by the computer system at the server, the server-side point cloud using an image of a camera of the mobile device, motion data of the mobile device, and orientation data of the camera that is associated with the image.
3. The medium of claim 2, wherein the motion data includes inertial measurement data from an inertial measurement unit of the mobile device and the orientation data includes pose-transform data.
4. The medium of claim 2, wherein point coordinates of points of the mobile station-side point cloud are changed with aid of the motion data or the orientation data evaluated by the server, in particular in that a drift of the point coordinates of the points on the mobile station-side point cloud is corrected.
5. The medium of claim 2, wherein the orientation data is corrected on by the server with aid of the motion data.
6. The medium of claim 2, wherein at least one of a feature recognition or a feature description is performed by the server in the image using multi-scale oriented patches (MOPS) or scale-invariant feature transform (SIFT).
7. The medium of claim 2, wherein features are learned on by the server during at least one of feature recognition or a feature description that use deep learning.
8. The medium of claim 2, wherein a bundle adjustment is performed on by the server in the image.
9. The medium of claim 2, wherein the operations further comprise:
determining, based on a server evaluation of the image, setting data for the camera; and
transmitting the setting data to the mobile device.
10. The medium of claim 1, wherein the server-side point cloud or the mobile station-side point cloud is generated using a simultaneous localization and mapping algorithm.
11. The medium of claim 1, wherein the server-side point cloud and the mobile station-side point cloud include respective point coordinates, points of the server-side point cloud and the mobile station-side point cloud correspond respectively to a point coordinate.
12. The medium of claim 11, wherein the point coordinates are represented by vectors.
13. The medium of claim 1, wherein during the combination of the server-side point cloud with the mobile station-side point cloud, at least one of the following is performed: points of the server-side point cloud are at least partially supplemented by points of the mobile station-side point cloud, point coordinates of the points of the server-side point cloud are at least partially converted with aid of point coordinates of the points of the mobile station-side point cloud, at least one of the points of the mobile station-side point cloud are at least partially supplemented by the points of the server-side point cloud, the point coordinates of the points of the mobile station-side point cloud are at least partially converted with aid of the point coordinates of the points of the server-side point cloud.
14. The medium of claim 1, wherein the operations further comprise:
removing, using statistical evaluation, an outlier from the mobile station-side point cloud.
15. The medium of claim 1, wherein the operations further comprise steps for generating the mobile station-side point cloud.
16. The medium of claim 1, wherein the operations further comprise:
determining, using the server-side point cloud, a loop closure; and
correcting, using the loop closure, a drift of points of the mobile station-side point cloud.
17. The medium of claim 16, wherein the correcting the drift includes a linear adjustment.
18. The medium of claim 1, wherein the operations further comprise:
operating, by the computer system, an augmented reality application using the server-side point cloud or the mobile station-side point cloud.
19. The medium of claim 1, wherein the operations further comprise:
determining at least two instances for the server-side point cloud, wherein in each instance at least one feature is learned by at least one of a feature recognition or a feature description by the server and the respective instances together with features are transmitted to the mobile device.
20. A method, comprising:
obtaining, by a computer system, a server-side point cloud generated by a server;
obtaining, by the computer system, a mobile station-side point cloud generated by a mobile device;
combining, by the computer system, at least one of the mobile station-side point cloud with data from the server-side point cloud to form an updated mobile station-side point cloud or the server-side point cloud with data from the mobile station-side point cloud to form an updated server-side point cloud; and
generating, by the computer system, at least a portion of an environment map from the updated server-side point cloud or the mobile station-side point cloud.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MAURICE L MCDOWELL, JR whose telephone number is (571)270-3707. The examiner can normally be reached Mon-Fri: 2pm-10pm.
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/MAURICE L. MCDOWELL, JR/Primary Examiner, Art Unit 2612
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