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 .
Priority
The instant application is the National Stage of the International Application No. PCT/JP2022/017663 filed on 04/13/2022. Thus, the effective filing date of Claims 1-13 are 04/13/2022.
Information Disclosure Statement
The information disclosure statements (“IDS”) filed on 09/27/2024 and 09/17/2025 was reviewed and the listed references were noted.
Drawings
The 16 page drawings have been considered and placed on record in the file.
Status of Claims
Claims 1-13 are currently pending.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent Claim 1 is directed to an apparatus that relates the displacement of points to the distribution of point cloud data associated to the points.
Step 1:
With regard to Step 1, the instant claim 1 is directed to an apparatus among the statutory categories of invention.
Step 2A – Prong 1:
With regard to Step 2A – Prong 1, for example in apparatus Claim 1, the limitations “…acquire a distribution of amount of displacement for points in point cloud data, and compose the amount of displacement to the points in the point cloud data according to the distribution.”, as recited, are an apparatus that, under its broadest reasonable interpretation, covers performance of the limitation in the mind/observation of a person to observe the distribution of cloud points related to the displacement of points. That is nothing in the claim steps preclude the limitations from practically being performed in the mind or through observation/judgement of a person to observe the distribution of cloud points derived from observed displacement. If a claim limitation, under its broadest reasonably interpretation covers performance of the limitation in the mind then it falls within the "Mental processes" grouping of the abstract idea, which include concepts performed in the human mind, including an observation, evaluation, judgement, opinion. Accordingly, the claim recites an abstract idea
Step 2A – Prong 2:
The 2019 PEG defines the phrase “integration into a practical application” to require an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception. In the instant case, there are no additional elements in the claims, which may apply, rely on, or use the judicial exception.
Step 2B:
Because the claim fails under Step 2A, the claim is further evaluated under Step 2B. The claim herein do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Accordingly, the claim is not patent eligible.
Further, with regard to dependent Claims 2-11 viewed individually, these additional elements are under their broadest reasonable interpretation, cover performance of the limitation in the mind and do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Accordingly, Claims 2-11 are rejected under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
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:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-4, 7, 9-10, and 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Nakamura (“Research on feature extraction techniques for point cloud data based on completed floor plans.” published on October 26, 2017) in view of Smolyanskiy (US 20210150230).
Consider Claim 1, Nakamura teaches “A deformation composition data generation apparatus comprising: (Nakamura; Pg. 4, Para. 2; “This function takes ground points, other points, and outline data of road features as input and outputs point cloud data of road surface features, point cloud data of features that share a region with the road surface, and point cloud data of 3D feature structures.”) “compose the amount of displacement to the points in the point cloud data according to the distribution.” (Nakamura; Figure 10-13 (See figures below)).
Nakamura does not explicitly disclose “a memory storing software instructions, and one or more processors configured to execute the software instructions to…”. However, in analogous field of endeavor, Smolyanskiy teaches “a memory storing software instructions, and one or more processors configured to execute the software instructions to…” (Smolyanskiy; [0098]; “For instance, various functions may be carried out by a processor executing instructions stored in memory.”). Accordingly, before the effective filing date of the instant application, it would have been obvious to one of ordinary skill in the art to combine Nakamura with the teachings of Smolyanskiy to further implement the point cloud perception methods in an apparatus. One of ordinary skill in the art would be motivated to combine Nakamura and Smolyanskiy to “provide a simple and effective way to detect and classify objects, and regress their dimensions and orientations” (Smolyanskiy; [0008]) in a real life application. Accordingly, the combination of Nakamura and Smolyanskiy discloses the invention of Claim 1.
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Consider Claim 2, the combination of Nakamura and Smolyanskiy teaches “The deformation composition data generation apparatus according to claim 1, wherein the distribution is a distribution of amount of displacement of each point in the point cloud data from a model representing a shape formed by the point cloud data in any range of the point cloud data.” (Nakamura; Figure 10-13 (See figures above)).
Consider Claim 3, the combination of Nakamura and Smolyanskiy teaches “The deformation composition data generation apparatus according to claim 2, wherein the one or more processors are further configured to execute the software instructions to
select the range where composition is performed on the point cloud data.” ((Nakamura; Figure 14-16 (See figured below)).
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Consider Claim 4, the combination of Nakamura and Smolyanskiy teaches “The deformation composition data generation apparatus according to claim 3, wherein the one or more processors are further configured to execute the software instructions to
generate the model for the selected range from the point cloud data.” (Nakamura; Figure 14-16 (See figures above)).
Consider Claim 7, the combination of Nakamura and Smolyanskiy teaches “The deformation composition data generation apparatus according to claim 1, wherein the one or more processors are further configured to execute the software instructions to perform a variation process on the distribution of amount of displacement.” (Smolyanskiy; [0072]; “By way of non-limiting example, instance regression head 660 may include separate dimensions identifying the x-dimension of the center of a detected object, the y-dimension of the center of a detected object, the width of a detected object, the height of a detected object (e.g., displacement from the ground), the sine of the orientation of a detected objected (e.g., a rotation angle in 2D image space), the cosine of the orientation of a detected object, and/or other types of information.” (emphasis added)). The proposed combination as well as the motivation for combining the Nakamura and Smolyanskiy references presented in the rejection of claim 1, apply to claim 7 and are incorporated herein by reference. Thus, the method recited in claim 7 is met by Nakamura and Smolyanskiy.
Consider Claim 9, the combination of Nakamura and Smolyanskiy teaches “The deformation composition data generation apparatus according to claim 1, further comprising a memory which stores the distribution of amount of displacement.” (Smolyanskiy; [0050]; “By way of nonlimiting example, different sensors 401 (whether the same type or a different of sensor) may be used to generate image data (e.g., LiDAR range image, camera images, etc.) having the same (e.g., perspective) view of the environment in a common image space, and image data from different sensors 401 or sensor modalities may be stored in separate channels of a tensor.”). The proposed combination as well as the motivation for combining the Nakamura and Smolyanskiy references presented in the rejection of claim 1, apply to claim 9 and are incorporated herein by reference. Thus, the method recited in claim 9 is met by Nakamura and Smolyanskiy.
Consider Claim 10, the combination of Nakamura and Smolyanskiy teaches “The deformation composition data generation apparatus according to claim 1,wherein the distribution of amount of displacement is a distribution generated by calculating an amount of displacement from existing point cloud data.” (Nakamura; Figure 10 (See figure above)).
Claim 12 recites a method with steps corresponding to the components of the apparatus recited in Claim 1. Therefore, the recited steps of this claim are mapped to the proposed combination in the same manner as the corresponding components in its corresponding apparatus claim. Additionally, the rationale and motivation to combine the Nakamura and Smolyanskiy references, presented in rejection of Claim 1, apply to this claim.
Claim 13 recites a non-transitory computer-readable recording medium storing a program with instructions corresponding to the components of the apparatus recited in Claim 1. Therefore, the recited programming instructions of this claim are mapped to the proposed combination in the same manner as the corresponding components in its corresponding apparatus claim. Additionally, the rationale and motivation to combine the Nakamura and Smolyanskiy references, presented in rejection of Claim 1, apply to this claim. Finally, the combination of Nakamura and Smolyanskiy discloses a computer readable storage medium (Smolyanskiy; [0242]; The memory 1704 may include any of a variety of computer-readable media. The computer-readable media may be any available media that may be accessed by the computing device 1700. The computer-readable media may include both volatile and nonvolatile media, and removable and non-removable media. By way of example, and not limitation, the computer-readable media may comprise computer-storage media and communication media.”).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Nakamura (“Research on feature extraction techniques for point cloud data based on completed floor plans.” published on October 26, 2017) in view of Smolyanskiy (US 20210150230) in further view of Jovančević, I. et. al. (“3D point cloud analysis for detection and characterization of defects on airplane exterior surface” published on October 17, 2017).
Consider Claim 5, the combination of Nakamura and Smolyanskiy teaches “The deformation composition data generation apparatus according to claim 4, (Smolyanskiy; [0098]; “For instance, various functions may be carried out by a processor executing instructions stored in memory.”) “
The combination of Nakamura and Smolyanskiy does not explicitly disclose “wherein the model represents a planar structure,” or “to generate the model by calculating an equation of a plane through which the points belonging to the range selected from the point cloud data pass.”. However, in an analogous field of endeavor, Jovančević teaches “wherein the model represents a planar structure,” (Jovančević; Fig. 3 (See image below)) and “to generate the model by calculating an equation of a plane through which the points belonging to the range selected from the point cloud data pass.” (Jovančević; Step 3 (Normals and Curvature Estimation); “By using a least-square plane fitting estimation algorithm as introduced in [47], we can determine the tangent plane S represented by a point x and a normal vector . For all the points , the distance from to the plane S is defined as:
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”). Accordingly, before the effective filing date of the instant application, it would have been obvious to one of ordinary skill in the art to Nakamura and Smolyanskiy with the teachings of Jovančević to further calculate an equation for the plane of the point cloud data. One of ordinary skill in the art would be motivated to combine Nakamura, Smolyanskiy, and Jovančević “for understanding the local properties of a geometric surface” (Jovančević, Step 3 (Normals and Curvature Estimation). Accordingly, the combination of Nakamura, Smolyanskiy, and Jovančević discloses the invention of Claim 5.
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Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Nakamura (“Research on feature extraction techniques for point cloud data based on completed floor plans.” published on October 26, 2017) in view of Smolyanskiy (US 20210150230) in further view of Rachakonda et. al. (“Methods and considerations to determine sphere center from terrestrial laser scanner point cloud data.” Published on September 6, 2017).
Consider Claim 6, the combination of Nakamura and Smolyanskiy teaches “The deformation composition data generation apparatus according to claim 4, wherein (Smolyanskiy; [0098]; “For instance, various functions may be carried out by a processor executing instructions stored in memory.”) “
The combination of Nakamura and Smolyanskiy does not explicitly disclose “the model represents a geometric structure of a spherical surface or cylinder,” or “generate the model by calculating an equation of the spherical surface or cylinder through which the points belonging to the range selected from the point cloud data pass, or a parameter characterizing the geometric structure.”. However, in an analogous field of endeavor, Rachakonda teaches the model represents a geometric structure of a spherical surface or cylinder,” (Rachakonda; Figure 2 (See figure below)), and “generate the model by calculating an equation of the spherical surface or cylinder through which the points belonging to the range selected from the point cloud data pass, or a parameter characterizing the geometric structure.” (Rachakonda; Formula 2 (See formula below); 2.1. Orthogonal non-linear least-squares method; “A non-linear least-squares algorithm is a method that attempts to minimize the sum of the squares of the orthogonal distances (called residuals) between a given set of points and the best fitted sphere surface.”). Accordingly, before the effective filing date of the instant application, it would have been obvious to one of ordinary skill in the art to Nakamura and Smolyanskiy with the teachings of Rachakonda to further determine point cloud perception of a spherical surface. One of ordinary skill in the art would be motivated to combine Nakamura, Smolyanskiy, and Rachakonda to create a more accurate and robust apparatus that can perform point cloud perception on various surface shapes. Accordingly, the combination of Nakamura, Smolyanskiy, and Rachakonda discloses the invention of Claim 6.
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Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Nakamura (“Research on feature extraction techniques for point cloud data based on completed floor plans.” published on October 26, 2017) in view of Smolyanskiy (US 20210150230) in further view of Sham (US 20230215044).
Consider Claim 8, the combination of Nakamura and Smolyanskiy teaches “The deformation composition data generation apparatus according to claim 1, wherein the one or more processors are further configured to execute the software instructions” (Smolyanskiy; [0098]; “For instance, various functions may be carried out by a processor executing instructions stored in memory.”)
The combination of Nakamura and Smolyanskiy does explicitly disclose “construct a learning model by performing machine learning using the point cloud data to which the amount of displacement is composed as training data.” However, in analogous field of endeavor, Sham teaches “construct a learning model by performing machine learning using the point cloud data to which the amount of displacement is composed as training data.” (Sham; [0013] "For example, when one sensor is a camera sensor and the other sensor is a lidar sensor, associations between sensor measurements can be used to generate training data for training a machine learning model, e.g., a deep neural network, that predicts three-dimensional object properties from an image alone."). Accordingly, before the effective filing date of the instant application, it would have been obvious to one of ordinary skill in the art to Nakamura and Smolyanskiy with the teachings of Sham to further generate training data from the displacement data to train a learning model. One of ordinary skill in the art would be motivated to combine Nakamura, Smolyanskiy, and Sham to improve the performance and accuracy of the learning model. Accordingly, the combination of Nakamura, Smolyanskiy, and Sham discloses the invention of Claim 8.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Nakamura (“Research on feature extraction techniques for point cloud data based on completed floor plans.” published on October 26, 2017) in view of Smolyanskiy (US 20210150230) in further view of Li et. al. (“A Comparison Method for 3D Laser Point Clouds in Displacement Change Detection for Arch Dams” published on March 20, 2021).
Consider Claim 11, the combination of Nakamura and Smolyanskiy does not explicitly disclose “The deformation composition data generation apparatus according to claim 1, wherein the distribution of amount of displacement is a distribution defined by a mathematical formula that expresses a relationship between coordinates of the points in the point cloud data and the amount of displacement.”. However, in an analogous field of endeavor, Li teaches “wherein the distribution of amount of displacement is a distribution defined by a mathematical formula that expresses a relationship between coordinates of the points in the point cloud data and the amount of displacement” (Li; Formula 1 (See formula below)). Accordingly, before the effective filing date of the instant application, it would have been obvious to one of ordinary skill in the art to Nakamura and Smolyanskiy with the teachings of Li to further define a mathematical relationship between the point cloud data coordinates and displacement. One of ordinary skill in the art would be motivated to combine Nakamura, Smolyanskiy, and Li “to analyze the displacement variation…in two states and improve the accuracy of comparing the two surfaces” (Li; Abstract). Accordingly, the combination of Nakamura, Smolyanskiy, and Li discloses the invention of Claim 11.
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Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Annie Pham whose telephone number is (571)272-1673. The examiner can be normally be reached Mon-Fri 9:00a – 5:00p.
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/ANNIE H PHAM/Examiner, Art Unit 2662
/Siamak Harandi/Primary Examiner, Art Unit 2662
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