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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/29/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Status
Claims 1-15 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-14 of U.S. Patent No. 12,190,534 B2.
Claim(s) 1-7, 12 and 15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Trouve et al (U.S. 20170270386 A1; Trouve).
Claim(s) 8-10 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Trouve et al (U.S. 20170270386 A1; Trouve), in view of Ellen M. Rathje et al, (“Remote sensing for geotechnical earthquake reconnaissance”; Ellen).
Claim(s) 11 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Trouve et al (U.S. 20170270386 A1; Trouve), in view of Kitamura et al, (“U.S. 20140037194”; Kitamura).
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 conflicting claims 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); 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 nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined 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 § 2146 et seq. 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 filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual 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 www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-15 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-14 of U.S. Patent No. 12,190,534 B2.
For Claim 1, although this claim is not identical to Claim 1 and 11 of U.S. Patent No. 12,190,534, this claim is not patentably distinct from Claim 1 and 11 of U.S. Patent No. 12,190,534 because Claim 1 is broader than and fully encompassed by Claim 1 and 11 of U.S. Patent No. 12,190,534.
Application 18/964,079 (U.S. 20250095171 A1)
US Patent 12,190,534 B2
An object amount calculation apparatus, comprising: a receiver configured to obtain a first three-dimensional model and a second three-dimensional model different from the first three-dimensional model, each of the first three-dimensional model and the second three-dimensional model representing a same space, each of the first three-dimensional model and the second three-dimensional model being constituted with regions each having an attribute; a user interface configured to receive an operation selecting, among at least two attributes of each of the first three-dimensional model and the second three-dimensional model, an attribute having higher priority than another attribute; and a processor configured to: align the first three-dimensional model and the second three-dimensional model based on the attribute selected by the operation; calculate a difference between the first three-dimensional model aligned and the second three-dimensional model aligned; and output an amount of the difference and an attribute corresponding to the difference among the at least two attributes.
An object amount calculation apparatus, comprising: a receiver configured to obtain a first three-dimensional model and a second three-dimensional model different from the first three-dimensional model, each of the first three-dimensional model and the second three-dimensional model representing a same space, the first three-dimensional model corresponding to a first point in time and the second three-dimensional model corresponding to a point in time different from the first point in time, each of the first three-dimensional model and the second three-dimensional model being constituted with regions having respective attributes, the object amount calculation apparatus further comprising: a processor configured to: extract at least one attribute of the first three-dimensional model and the second three-dimensional model; align the first three-dimensional model and the second three-dimensional model based on the at least one attribute of the first three-dimensional model and the second three-dimensional model that has been extracted, wherein the at least one attribute is information indicating a result of recognition of an object type in a respective region in the first three-dimensional model and the second three-dimensional model; calculate, for each of the attributes, a difference between the first three-dimensional model aligned and the second three-dimensional model aligned, wherein the difference includes an attribute of the first three-dimensional model and the second three-dimensional model that shows a change between the first three-dimensional model and the second three-dimensional model; and output (i) a total amount of differences corresponding to two or more attributes among the attributes and (ii) information on the two or more attributes.
For Claims 2-15, although this claim is not identical to Claims 2-10 and 12-14 of U.S. Patent No. 12,190,534, this claim is not patentably distinct from Claims 2-10 and 12-14 of U.S. Patent No. 12,190,534 because Claims 2-15 are broader than and fully encompassed by Claims 2-10 and 12-14 of U.S. Patent No. 12,190,534.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
(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) 1-7, 12 and 15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Trouve et al (U.S. 20170270386 A1; Trouve).
Regarding claim 1, Trouve discloses An object amount calculation apparatus, (Paragraph 8: “a computer system environment suitable for operation … the 3D comparison program 101 may exist in a cloud-based, virtual, or distributed environment, or a remote environment on defined server hardware.”) comprising:
a receiver (Fig.1: 3D comparison program 101) configured to obtain a first three-dimensional model (Fig.1: First 3D model 102) and a second three-dimensional model (Fig.1: Second 3D model 103) different from the first three-dimensional model, each of the first three-dimensional model and the second three-dimensional model representing a same space, (Paragraph 9: “Within a computer system 100, a 3D comparison program 101 may receive a first 3D model 102 and a second 3D model 103. In 3D computer graphics, 3D modeling may be understood as the process of developing a mathematical representation of any three-dimensional surface of an object.”; Paragraph 13: “The 3D comparison program 101 may reconstruct the first set of ten digital images into a first 3D model 102 (e.g., wire frame model) and the second set of ten digital images into a second 3D model 103 (e.g., polygon-based model) using a Voxel Coloring Algorithm.”)
each of the first three-dimensional model and the second three-dimensional model being constituted with regions each having an attribute; (Paragraph 11: “The first 3D model 102 and the second 3D model 103 may further include a first set of objects 104 and a second set of objects 105, respectively. Each object of the first set of objects 104 and said second set of objects 105 may further include one or more attributes 110 (e.g., color, texture, shape, position, volume, etc.).”; Paragraph 14: “The 3D comparison program 101 may scan a 3D model to identify a set of objects or the absence of one or more objects by any generally known image segmentation methods, including, but not limited to clustering methods, compression-based methods, edge detection methods, etc.”)
a user interface configured to receive an operation selecting, among at least two attributes of each of the first three-dimensional model and the second three-dimensional model, an attribute having higher priority than another attribute; (Paragraph 17: “the 3D comparison program 101 may assign a weighted value 111 (e.g., a number between zero and one) to an attribute 110 based on the importance of the attribute 110. The assignment of a weighted value 111 to each attribute 110 may initially be determined by a user based on the importance of the attribute 110 with respect to a given user. For example, the attribute 110 “scratch or dent” of an object may be given a weighted value 110 of 0.75, the attribute 110 “change in color” of the object may be given a weighted value 111 of 1, and the attribute 107 “change in position” of the object may be given a weighted value 111 of 0.5”; Paragraph 20: “he 3D comparison program may use an SVM to produce classification models in which each feature or attribute 110 is given a weight. The more important attributes 110 are assigned a higher weight, while less important attributes 110 are given a lower weight. The weights may be assigned based on domain knowledge about the relative importance of the attributes 110. The relative importance of the attributes 110 may be determined based on the user either accepting or rejecting the one or more differences 107”.) and
a processor Fig.3: one or more processor 304; Paragraph 23: “a computer 300 suitable for executing the 3D comparison program 101, … one or more processor(s) 304 (including one or more computer processors)”) configured to: align the first three-dimensional model and the second three-dimensional model based on the attribute selected by the operation; Paragraph 10: “the 3D comparison program 101 may identify at least one common object 106 between the first set of objects 104 and the second set of objects 105. The 3D comparison program 101 may further compare the first set of objects 104 to the second set of objects 105 to yield one or more differences 107.”; Paragraph 11: “Each object of the first set of objects 104 and said second set of objects 105 may further include one or more attributes 110 (e.g., color, texture, shape, position, volume, etc.)”).
calculate a difference between the first three-dimensional model aligned and the second three-dimensional model aligned; ; (Paragraph 10: “The 3D comparison program 101 may further compare the first set of objects 104 to the second set of objects 105 to yield one or more differences 107.”; Paragraph 15: “the 3D comparison program 101 may compare the first set of objects 104 and the second set of objects 105 by calculating a measurement of change between an attribute 110 of a common object 106 between the first set of objects 104 and the second set of objects 105.” ) and
output an amount of the difference and an attribute corresponding to the difference among the at least two attributes. (Paragraph 10: “The 3D comparison program 101 may further sort each of the one or more differences 107 based on a set of rules 108 to yield a list of differences 109.” ; Paragraph 17: “the set of rules 108 may further include a rule to sort each of the one or more differences 107 based on the weighted 111 value of the attribute 110 … the attribute 110 “scratch or dent” of an object may be given a weighted value 110 of 0.75, the attribute 110 “change in color” of the object may be given a weighted value 111 of 1”; Paragraph 19: “each of the one or more differences 107 presented in the list of differences 109 may be either accepted or rejected.”)
Regarding claim 2, Trouve discloses the attribute corresponding to the difference indicates that the difference is a mixture. (Paragraph 10: “The one or more differences 107 may be the result in the change of one or more common objects 106 of a first environment, represented by the first 3D model 102 and a second environment, represented by the second 3D model 103, over a given period of time.”)
Regarding claim 3, Trouve discloses the attribute corresponding to the difference indicates that the difference is a natural object or a man-made object. (Paragraph 11: “Each object of the first set of objects 104 and said second set of objects 105 may further include one or more attributes 110 (e.g., color, texture, shape, position, volume, etc.)”); Paragraph 21: “the 3D comparison program 101 may determine a pattern wherein the user repeatedly accepts a difference 107 of three inches or more for the attribute 110 “scratch or dent” for a common object 106 “table,” but rejects a difference 107 of less than six inches for the attribute 110 “scratch or dent” for a common object 106 “wall.” ”)”)
Regarding claim 4, Trouve discloses the processor is further configured to: generate at least one of the first three-dimensional model or the second three-dimensional model from a plurality of images each representing the same space. (Paragraph 13: “the 3D comparison program 101 may receive a first set of ten digital images of an apartment living room taken with a digital camera at a first instance and a second set of ten digital images of the same apartment living room taken with a digital camera at a second instance. Each successive digital image of each set of ten digital images may overlap the previous image. The 3D comparison program 101 may reconstruct the first set of ten digital images into a first 3D model 102 (e.g., wire frame model) and the second set of ten digital images into a second 3D model 103 (e.g., polygon-based model) using a Voxel Coloring Algorithm.”)
Regarding claim 5, Trouve discloses when the difference has two or more attributes, the processor is configured to classify the two or more attributes according to type, and output classified attributes to cause a display apparatus to collectively display the two or more attributes on a type-by-type basis. (Paragraph 18: “the set of rules 108 may further include a rule to sort each of the one or more differences 107 based on a relevance score 112. The relevance score 112 may be calculated by multiplying the measurement of change between a common object 106 between the first set objects 104 and the second set of objects 105 by the weighted value 111 of the attribute 110 associated with the common object 106. For example, the 3D comparison program 101 may calculate a measurement of change of four inches between a common object 106 for the attribute 110 “scratch or dent” … calculate a measurement of change of ten inches between a common object 106 for the attribute 110 “change in position”.”; Paragraph 20: “he 3D comparison program may use an SVM to produce classification models in which each feature or attribute 110 is given a weight. The more important attributes 110 are assigned a higher weight, while less important attributes 110 are given a lower weight. The weights may be assigned based on domain knowledge about the relative importance of the attributes 110. The relative importance of the attributes 110 may be determined based on the user either accepting or rejecting the one or more differences 107)
Regarding claim 6, Trouve discloses the processor is configured to calculate the amount of the difference on the type-by-type basis. (Paragraph 18: “the set of rules 108 may further include a rule to sort each of the one or more differences 107 based on a relevance score 112. The relevance score 112 may be calculated by multiplying the measurement of change between a common object 106 between the first set objects 104 and the second set of objects 105 by the weighted value 111 of the attribute 110 associated with the common object 106. For example, the 3D comparison program 101 may calculate a measurement of change of four inches between a common object 106 for the attribute 110 “scratch or dent” … calculate a measurement of change of ten inches between a common object 106 for the attribute 110 “change in position”.”)
Regarding claim 7, Trouve discloses the amount of the difference is at least one of a volume or a weight of the difference. ((Paragraph 18: “the set of rules 108 may further include a rule to sort each of the one or more differences 107 based on a relevance score 112. The relevance score 112 may be calculated by multiplying the measurement of change between a common object 106 between the first set objects 104 and the second set of objects 105 by the weighted value 111 of the attribute 110 associated with the common object 106. For example, the 3D comparison program 101 may calculate a measurement of change of four inches between a common object 106 for the attribute 110 “scratch or dent” … calculate a measurement of change of ten inches between a common object 106 for the attribute 110 “change in position”.”)
Regarding claim 12, Trouve discloses An object amount calculation method, (Paragraph 8: “a computer system environment suitable for operation … the 3D comparison program 101 may exist in a cloud-based, virtual, or distributed environment, or a remote environment on defined server hardware.”) comprising:
obtaining a first three-dimensional model and a second three-dimensional model different from the first three-dimensional model, each of the first three-dimensional model and the second three-dimensional model representing a same space, (Paragraph 9: “Within a computer system 100, a 3D comparison program 101 may receive a first 3D model 102 and a second 3D model 103. In 3D computer graphics, 3D modeling may be understood as the process of developing a mathematical representation of any three-dimensional surface of an object.”; Paragraph 13: “The 3D comparison program 101 may reconstruct the first set of ten digital images into a first 3D model 102 (e.g., wire frame model) and the second set of ten digital images into a second 3D model 103 (e.g., polygon-based model) using a Voxel Coloring Algorithm.”)
each of the first three-dimensional model and the second three-dimensional model being constituted with regions each having an attribute; (Paragraph 11: “The first 3D model 102 and the second 3D model 103 may further include a first set of objects 104 and a second set of objects 105, respectively. Each object of the first set of objects 104 and said second set of objects 105 may further include one or more attributes 110 (e.g., color, texture, shape, position, volume, etc.).”; Paragraph 14: “The 3D comparison program 101 may scan a 3D model to identify a set of objects or the absence of one or more objects by any generally known image segmentation methods, including, but not limited to clustering methods, compression-based methods, edge detection methods, etc.”)
receiving, by a user interface, an operation selecting, among at least two attributes of each of the first three-dimensional model and the second three-dimensional model, an attribute having higher priority than another attribute; (Paragraph 17: “the 3D comparison program 101 may assign a weighted value 111 (e.g., a number between zero and one) to an attribute 110 based on the importance of the attribute 110. The assignment of a weighted value 111 to each attribute 110 may initially be determined by a user based on the importance of the attribute 110 with respect to a given user. For example, the attribute 110 “scratch or dent” of an object may be given a weighted value 110 of 0.75, the attribute 110 “change in color” of the object may be given a weighted value 111 of 1, and the attribute 107 “change in position” of the object may be given a weighted value 111 of 0.5”; Paragraph 20: “he 3D comparison program may use an SVM to produce classification models in which each feature or attribute 110 is given a weight. The more important attributes 110 are assigned a higher weight, while less important attributes 110 are given a lower weight. The weights may be assigned based on domain knowledge about the relative importance of the attributes 110. The relative importance of the attributes 110 may be determined based on the user either accepting or rejecting the one or more differences 107”.)
aligning the first three-dimensional model and the second three-dimensional model based on the attribute selected by the operation; Paragraph 10: “the 3D comparison program 101 may identify at least one common object 106 between the first set of objects 104 and the second set of objects 105. The 3D comparison program 101 may further compare the first set of objects 104 to the second set of objects 105 to yield one or more differences 107.”; Paragraph 11: “Each object of the first set of objects 104 and said second set of objects 105 may further include one or more attributes 110 (e.g., color, texture, shape, position, volume, etc.)”).
calculating a difference between the first three-dimensional model and the second three-dimensional model which are aligned in the aligning; (Paragraph 10: “The 3D comparison program 101 may further compare the first set of objects 104 to the second set of objects 105 to yield one or more differences 107.”; Paragraph 15: “the 3D comparison program 101 may compare the first set of objects 104 and the second set of objects 105 by calculating a measurement of change between an attribute 110 of a common object 106 between the first set of objects 104 and the second set of objects 105.” ) and
outputting and an attribute corresponding to the difference among the at least two attributes. (Paragraph 10: “The 3D comparison program 101 may further sort each of the one or more differences 107 based on a set of rules 108 to yield a list of differences 109.” ; Paragraph 17: “the set of rules 108 may further include a rule to sort each of the one or more differences 107 based on the weighted 111 value of the attribute 110 … the attribute 110 “scratch or dent” of an object may be given a weighted value 110 of 0.75, the attribute 110 “change in color” of the object may be given a weighted value 111 of 1”; Paragraph 19: “each of the one or more differences 107 presented in the list of differences 109 may be either accepted or rejected.”)
Regarding claim 15, Trouve discloses A non-transitory computer-readable recording medium for use in a computer, the recording medium having a computer program recorded thereon for causing the computer to execute an object amount calculation method (Paragraph 26: “Program instructions for the 3D comparison program 101 may be stored in the persistent storage 308, or more generally, any computer readable storage media, for execution by one or more of the respective computer processors 304 via one or more memories of the memory 306.”) including:
obtaining a first three-dimensional model and a second three-dimensional model different from the first three-dimensional model, each of the first three-dimensional model and the second three-dimensional model representing a same space, (Paragraph 9: “Within a computer system 100, a 3D comparison program 101 may receive a first 3D model 102 and a second 3D model 103. In 3D computer graphics, 3D modeling may be understood as the process of developing a mathematical representation of any three-dimensional surface of an object.”; Paragraph 13: “The 3D comparison program 101 may reconstruct the first set of ten digital images into a first 3D model 102 (e.g., wire frame model) and the second set of ten digital images into a second 3D model 103 (e.g., polygon-based model) using a Voxel Coloring Algorithm.”)
each of the first three-dimensional model and the second three-dimensional model being constituted with regions each having an attribute; (Paragraph 11: “The first 3D model 102 and the second 3D model 103 may further include a first set of objects 104 and a second set of objects 105, respectively. Each object of the first set of objects 104 and said second set of objects 105 may further include one or more attributes 110 (e.g., color, texture, shape, position, volume, etc.).”; Paragraph 14: “The 3D comparison program 101 may scan a 3D model to identify a set of objects or the absence of one or more objects by any generally known image segmentation methods, including, but not limited to clustering methods, compression-based methods, edge detection methods, etc.”)
receiving, by a user interface, an operation selecting, among at least two attributes of each of the first three-dimensional model and the second three-dimensional model, an attribute having higher priority than another attribute; (Paragraph 17: “the 3D comparison program 101 may assign a weighted value 111 (e.g., a number between zero and one) to an attribute 110 based on the importance of the attribute 110. The assignment of a weighted value 111 to each attribute 110 may initially be determined by a user based on the importance of the attribute 110 with respect to a given user. For example, the attribute 110 “scratch or dent” of an object may be given a weighted value 110 of 0.75, the attribute 110 “change in color” of the object may be given a weighted value 111 of 1, and the attribute 107 “change in position” of the object may be given a weighted value 111 of 0.5”; Paragraph 20: “he 3D comparison program may use an SVM to produce classification models in which each feature or attribute 110 is given a weight. The more important attributes 110 are assigned a higher weight, while less important attributes 110 are given a lower weight. The weights may be assigned based on domain knowledge about the relative importance of the attributes 110. The relative importance of the attributes 110 may be determined based on the user either accepting or rejecting the one or more differences 107”.)
aligning the first three-dimensional model and the second three-dimensional model based on the attribute selected by the operation; Paragraph 10: “the 3D comparison program 101 may identify at least one common object 106 between the first set of objects 104 and the second set of objects 105. The 3D comparison program 101 may further compare the first set of objects 104 to the second set of objects 105 to yield one or more differences 107.”; Paragraph 11: “Each object of the first set of objects 104 and said second set of objects 105 may further include one or more attributes 110 (e.g., color, texture, shape, position, volume, etc.)”).
calculating a difference between the first three-dimensional model and the second three-dimensional model which are aligned in the aligning; (Paragraph 10: “The 3D comparison program 101 may further compare the first set of objects 104 to the second set of objects 105 to yield one or more differences 107.”; Paragraph 15: “the 3D comparison program 101 may compare the first set of objects 104 and the second set of objects 105 by calculating a measurement of change between an attribute 110 of a common object 106 between the first set of objects 104 and the second set of objects 105.” ) and
outputting and an attribute corresponding to the difference among the at least two attributes. (Paragraph 10: “The 3D comparison program 101 may further sort each of the one or more differences 107 based on a set of rules 108 to yield a list of differences 109.” ; Paragraph 17: “the set of rules 108 may further include a rule to sort each of the one or more differences 107 based on the weighted 111 value of the attribute 110 … the attribute 110 “scratch or dent” of an object may be given a weighted value 110 of 0.75, the attribute 110 “change in color” of the object may be given a weighted value 111 of 1”; Paragraph 19: “each of the one or more differences 107 presented in the list of differences 109 may be either accepted or rejected.”)
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 8-10 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Trouve et al (U.S. 20170270386 A1; Trouve), in view of Ellen M. Rathje et al, (“Remote sensing for geotechnical earthquake reconnaissance”; Ellen).
Regarding claim 8, Trouve discloses all the claims invention except wherein the processor is configured to extract a partial model from the first three-dimensional model and a partial model from the second three-dimensional model which have a common attribute, align the partial models by shifting the partial models to align coordinates of corresponding positions in the partial models, and subsequently align the first three-dimensional model and the second three-dimensional model by shifting the first three-dimensional model and the second three-dimensional model in accordance with a shift of the partial models.
Ellen discloses the processor is configured to extract a partial model from the first three-dimensional model (3.3.2: “split into smaller spatial cells”) and a partial model from the second three-dimensional model (3.3.2: “split into smaller spatial cells”) which have a common attribute, align the partial models by shifting the partial models to align coordinates of corresponding positions in the partial models, and subsequently align (3.3.2: “translation and rotation”) the first three-dimensional model and the second three-dimensional model by shifting the first three-dimensional model and the second three-dimensional model in accordance with a shift of the partial models. (3.3.2. Vertical and three-dimensional differencing: “ICP) technique [3] or its variants (e.g., [47]). ICP computes the 3D rigid body translation and rotation required to minimize the sum of the squared error between the two point clouds. As noted earlier, 3D features or texture must be present in the point clouds to accurately measure horizontal displacement from point clouds or DEM … develop a displacement field across a study area using ICP, the point clouds are split into smaller spatial cells (e.g., 100 m by 100 m) and the translation and rotation are computed for each cell.”)
Therefore, it would been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Trouve by including Geotechnical application areas for remote sensing that is taught by Ellen, to make the invention that Remote sensing for geotechnical earthquake reconnaissance; thus, one of ordinary skilled in the art would have been motivated to combine the references since this will improving three-dimensional digital elevation models of failure geometries as well as developing pre-event 3D models form pre-event digital photographs taken from different cameras and at different times.
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filling date of the claimed invention.
Regarding claim 9, Trouve discloses all the claims invention except the processor is configured to align the first three-dimensional model and the second three-dimensional model in a partial region which is a part of the same space, based on a first partial attribute that the first three-dimensional model has for the partial region and a second partial attribute that the second three-dimensional model has for the partial region, the second partial attribute being same as the first partial attribute.
Ellen discloses the processor is configured to align the first three-dimensional model and the second three-dimensional model in a partial region which is a part of the same space, based on a first partial attribute that the first three-dimensional model has for the partial region and a second partial attribute that the second three-dimensional model has for the partial region, the second partial attribute being same as the first partial attribute. (3.3.2. Vertical and three-dimensional differencing: “ICP) technique [3] or its variants (e.g., [47]). ICP computes the 3D rigid body translation and rotation required to minimize the sum of the squared error between the two point clouds. As noted earlier, 3D features or texture must be present in the point clouds to accurately measure horizontal displacement from point clouds or DEM … develop a displacement field across a study area using ICP, the point clouds are split into smaller spatial cells (e.g., 100 m by 100 m) and the translation and rotation are computed for each cell. … Fig. 7c showing the displacement vector amplitudes. The largest computed displacements (2to 3 m) occurred at the edges of the main scarp, and these areas represent zones of sloughing that occurred between acquisition of the two sets of images).
Therefore, it would been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Trouve by including Geotechnical application areas for remote sensing that is taught by Ellen, to make the invention that Remote sensing for geotechnical earthquake reconnaissance; thus, one of ordinary skilled in the art would have been motivated to combine the references since this will improving three-dimensional digital elevation models of failure geometries as well as developing pre-event 3D models form pre-event digital photographs taken from different cameras and at different times.
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filling date of the claimed invention.
Regarding claim 10, Trouve, as modified by Ellen, discloses all the claims invention. Ellen further discloses the processor is configured to shift at least one of the first three-dimensional model or the second three-dimensional model of the same space other than the partial region, in accordance with a shift of at least one of the first three-dimensional model or the second three-dimensional model resulting from alignment of the first three-dimensional model and the second three-dimensional model in the partial region. (3.3.2. Vertical and three-dimensional differencing: “ICP) technique [3] or its variants (e.g., [47]). ICP computes the 3D rigid body translation and rotation required to minimize the sum of the squared error between the two point clouds. As noted earlier, 3D features or texture must be present in the point clouds to accurately measure horizontal displacement from point clouds or DEM … develop a displacement field across a study area using ICP, the point clouds are split into smaller spatial cells (e.g., 100 m by 100 m) and the translation and rotation are computed for each cell.”).
Regarding claim 13, Trouve discloses all the claims invention except wherein , in the obtaining, the first three-dimensional model representing the same space before inflow of earth and the second three-dimensional model representing the same space after the inflow of the earth are obtained, and in the calculating, an amount of the earth is calculated as the amount of the difference.
Ellen discloses in the obtaining, the first three-dimensional model representing the same space before inflow of earth and the second three-dimensional model representing the same space after the inflow of the earth are obtained, and in the calculating, an amount of the earth is calculated as the total amount of the differences. (Fig,12 and 4.3. Ground movements due to liquefaction remediation near Lake Havasu City, US: “From this analysis, the average induced subsidence across the entire liquefaction remediation site was approximately 38 cm, which was within about 1 cm of the estimated average subsidence based on measured crater depths. Additionally, the volumetric change across the improvement zone was calculated as approximately 2395 m3”).
Therefore, it would been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Trouve by including Geotechnical application areas for remote sensing that is taught by Ellen, to make the invention that Remote sensing for geotechnical earthquake reconnaissance; thus, one of ordinary skilled in the art would have been motivated to combine the references since this will improving three-dimensional digital elevation models of failure geometries as well as developing pre-event 3D models form pre-event digital photographs taken from different cameras and at different times.
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filling date of the claimed invention.
Claim(s) 11 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Trouve et al (U.S. 20170270386 A1; Trouve), in view of Kitamura et al, (“U.S. 20140037194”; Kitamura).
Regarding claim 11, Trouve discloses all the claims invention except the processor is further configured to: extract an attribute of the first three-dimensional model and an attribute of the second three-dimensional model in a state in which the first three-dimensional model and the second three-dimensional model are not aligned, and in aligning the first three-dimensional model and the second three-dimensional model, the processor is configured to use the attribute of the first three-dimensional model extracted and the attribute of the second three-dimensional model extracted.
Kitamura discloses extract an attribute of the first three-dimensional model and an attribute of the second three-dimensional model in a state in which the first three-dimensional model and the second three-dimensional model are not aligned, (Fig. 3A-3B and Paragraph 88 : “ First, data of the planes of each of the three-dimensional models, which are already extracted by the plane labeling unit 203 in FIG. 2, are obtained. Then, top "n" planes are selected from the planes that form each of the three-dimensional models, in order of area. The number of "n" is freely selected, but in this case, n=4 for ease of explanation. In this example, the top 4 planes 401, 402, 403, and 404 are extracted from the planes that form the three-dimensional model 400. In addition, the top 4 planes 405, 406, 407, and 408 are extracted from the planes that form the three-dimensional model 400' of the object. Thus, the target to be processed is limited based on the area.”) and
in aligning the first three-dimensional model and the second three-dimensional model, the processor is configured to use the attribute of the first three-dimensional model extracted and the attribute of the second three-dimensional model extracted. (Paragraphs 89-93: “Next, the degree of similarity (matching) of the shape between the planes 401, 402, 403, and 404 of the first group and the planes 405, 406, 407, 408 of the second group is calculated. … calculating the similarity of the shape as exemplified in Tables 1 and 2, the similarity of the planes are roughly evaluated. The processing described above is performed by the similarity evaluating unit 103. The processing of the similarity evaluating unit 103 determines that, for example, the plane 401 is similar to the plane 405 or 406, and the plane 403 is similar to the plane 407 or 408.”; Paragraph 107: “When the processing is started (step S301), transformation matrixes that are necessary to adjust one matching plane to the other matching plane are calculated (step S302). For example, in the case shown in FIGS. 3A and 3B, transformation matrixes are calculated so as to perform rigid-body transformation by adjusting the positions of the centers of gravity of the planes 401 and 405 and aligning the normal directions of the two planes.”)
Therefore, it would been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Trouve by including three-dimensional point cloud position data that are measured at two different viewpoints that is taught by Kitamura, to make the invention that measuring three-dimensional information; thus, one of ordinary skilled in the art would have been motivated to combine the references since this will improving process three-dimensional point cloud position data that are obtained at different viewpoints as matching planes at very high accuracy as well as decreasing unnecessary processing such as calculations of the relationships between data for which the positions do not correspond with each other and the calculation is performed at high accuracy.
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filling date of the claimed invention.
Regarding claim 14, Trouve discloses all the claims invention except further comprising: extracting an attribute of the first three-dimensional model and an attribute of the second three-dimensional model in a state in which the first three-dimensional model and the second three-dimensional model are not aligned, wherein in the aligning, the first three-dimensional model and the second three-dimensional model are aligned using the attribute of the first three-dimensional model extracted and the attribute of the second three-dimensional model extracted.
Kitamura discloses extracting an attribute of the first three-dimensional model and an attribute of the second three-dimensional model in a state in which the first three-dimensional model and the second three-dimensional model are not aligned, (Fig. 3A-3B and Paragraph 88 : “ First, data of the planes of each of the three-dimensional models, which are already extracted by the plane labeling unit 203 in FIG. 2, are obtained. Then, top "n" planes are selected from the planes that form each of the three-dimensional models, in order of area. The number of "n" is freely selected, but in this case, n=4 for ease of explanation. In this example, the top 4 planes 401, 402, 403, and 404 are extracted from the planes that form the three-dimensional model 400. In addition, the top 4 planes 405, 406, 407, and 408 are extracted from the planes that form the three-dimensional model 400' of the object. Thus, the target to be processed is limited based on the area.”) wherein in the aligning, the first three-dimensional model and the second three-dimensional model are aligned using the attribute of the first three-dimensional model extracted and the attribute of the second three-dimensional model extracted. (Paragraphs 89-93: “Next, the degree of similarity (matching) of the shape between the planes 401, 402, 403, and 404 of the first group and the planes 405, 406, 407, 408 of the second group is calculated. … calculating the similarity of the shape as exemplified in Tables 1 and 2, the similarity of the planes are roughly evaluated. The processing described above is performed by the similarity evaluating unit 103. The processing of the similarity evaluating unit 103 determines that, for example, the plane 401 is similar to the plane 405 or 406, and the plane 403 is similar to the plane 407 or 408.”; Paragraph 107: “When the processing is started (step S301), transformation matrixes that are necessary to adjust one matching plane to the other matching plane are calculated (step S302). For example, in the case shown in FIGS. 3A and 3B, transformation matrixes are calculated so as to perform rigid-body transformation by adjusting the positions of the centers of gravity of the planes 401 and 405 and aligning the normal directions of the two planes.”)
Therefore, it would been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Trouve by including three-dimensional point cloud position data that are measured at two different viewpoints that is taught by Kitamura, to make the invention that measuring three-dimensional information; thus, one of ordinary skilled in the art would have been motivated to combine the references since this will improving process three-dimensional point cloud position data that are obtained at different viewpoints as matching planes at very high accuracy as well as decreasing unnecessary processing such as calculations of the relationships between data for which the positions do not correspond with each other and the calculation is performed at high accuracy.
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filling date of the claimed invention.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tateno et al (U.S. 20110206274 A1), “Position and Orientation Estimation Apparatus and Position and Orientation Estimation Method”, teaches about a position and orientation estimation apparatus inputs an image capturing an object, inputs a distance image including three-dimensional coordinate data representing the object, extracts an image feature from the captured image, determines whether the image feature represents a shape of the object based on three-dimensional coordinate data at a position on the distance image corresponding to the image feature, correlates the image feature representing the shape of the object with a part of a three dimensional model representing the shape of the object, and estimates the position and orientation of the object based on a correlation result.
Karasudani (U.S. 20170094244 A1), “Image Processing Device and Image Processing Method”, teaches about a method includes determining overlap between a three-dimensional model of a space in which objects are arranged and first three-dimensional information acquired from a distance sensor at a first time point, the distance sensor being along with a camera which captures an image of the space, determining another overlap between the three-dimensional model, the first three-dimensional information, and second three-dimensional information
acquired from the distance sensor at a second time point after the first time point.
Urisaka et al (U.S. 20060033733 A1), “Method, Apparatus And Program Processing A Three-dimensional Image”, teaches about n three-dimensional measurement apparatus, and a three-dimensional image processing method which conveys the surface features, including glossiness, and the three-dimensionality of a target object to a user taking into consideration not only the shape, the texture, and the color of the target object, but also an observation environment during the reconstruction of the image, namely, the shape, the position, and the color of a light source, and the position and the direction of the user with respect to the object.
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/DUY TRAN/Examiner, Art Unit 2674
/ONEAL R MISTRY/Supervisory Patent Examiner, Art Unit 2674
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