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
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on April 2, 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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) 1-6 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by (Japanese Patent JP-5698815-B2).
Regarding claim 1, JP-5698815-B2 discloses an object recognition device (Figure 1)
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comprising: an image acquisition unit which acquires a first image including two-dimensional pixels (page 3, highlighted excerpts below);
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a three-dimensional shape approximation determination unit which determines whether image information of a predetermined rectangular region in the first image is approximatable to predetermined three-dimensional shape information (Figure 1, 140 serves as 3D shape approximation; page 5, highlighted excerpts below);
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an image region estimation unit which cuts out the rectangular region as a first estimation region based on a determination result of the three-dimensional shape approximation determination unit (page 5, highlighted excerpts below e.g., arbitrary rectangular region could be region for estimation of 3D shape);
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and a region selection unit which selects a region having a smallest area of the first estimation region from among a plurality of the first estimation regions (page 5, highlighted excerpts above e.g., search region having the shortest distance from the projection point of the measurement point may be selected).
Regarding claim 2, JP-5698815-B2 further discloses the object recognition device according to claim 1, wherein the three- dimensional shape information is at least one of a box shape, a cylindrical shape, a conical shape, a triangular prism shape, a triangular pyramid shape, a quadrangular pyramid shape, a sphere shape, and a torus shape, and includes a shape expressed by a combination of the three- dimensional shape information (Figure 5 below, the 3D model has a shape representative of one of the enumerated shapes as claimed).
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Regarding claim 3, JP-5698815-B2 further discloses the object recognition device according to claim 1, wherein the image acquisition unit generates at least one rotated image obtained by rotating the first image, and uses the rotated image as the first image (page 4, highlighted excerpt below e.g., “six degrees of freedom” for 2D image acquisition).
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**Regarding claim 4, JP-5698815-B2 further discloses the object recognition device according to claim 3, wherein n (1 n N) rotated images are generated for each fixed discrete rotation angle value (page 4, highlighted excerpt below e.g. “the model holding unit 130 holds three-dimensional geometric model data of a target object and geometric features of the model are then uniformly sampled from each NURBS curved surface”).
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Regarding claim 5, JP-5698815-B2 further discloses the object recognition device according to claim 1, wherein the image acquisition unit acquires at least one first image by rotating an image sensor about an optical axis direction of the image sensor when the first image is acquired from the image sensor (page 4, highlighted excerpt above e.g., “six degrees of freedom” for 2D image acquisition).
Regarding claim 6, JP-5698815-B2 further discloses the object recognition device according to claim 5, wherein the image sensor is rotated n times (1 n N) for each fixed discrete rotation angle value (page 4, highlighted excerpt above e.g. “the model holding unit 130 holds three-dimensional geometric model data of a target object and geometric features of the model are then uniformly sampled from each NURBS curved surface”).
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:
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) 7-9, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over (Japanese Patent JP-5698815-B2) in view of Amano et. al. (United States Patent 2022/0092330 A1).
Regarding claim 7, JP-5698815-B2 discloses the object recognition device according to claim 1. However, JP-5698815-B2 fails to disclose wherein the three-dimensional shape approximation determination unit determines whether to approximate to the predetermined three-dimensional shape information using a training device trained by using a second image including a general object approximatable to the predetermined three- dimensional shape information, information indicating a rectangular region including the general object in the second image, and the predetermined three-dimensional shape information as training data.
Amano et. al. discloses wherein the three-dimensional shape approximation determination unit determines whether to approximate to the predetermined three-dimensional shape information using a training device trained by using a second image (Amano et. al. [0007] the storage section of the image processing device stores three-dimensional positional information for multiple feature points of a target object and an extraction process section extracts feature amounts and two-dimensional positional information from a two-dimensional image of the target object captured by a camera) including a general object approximatable to the predetermined three- dimensional shape information, information indicating a rectangular region including the general object in the second image (Amano et. al. Figure 5, [0027] the multiple viewpoints of the object are a total of nine viewpoints defined as the vertices or the midpoints of each side of a rectangular area), and the predetermined three-dimensional shape information as training data (Amano et. al. [0028] the feature points P is extracted from each two-dimensional image Gi by using a machine learning deep neural network (DNN).
It is necessary for the claimed invention to extract the 2D information from the 3D information to determine the object parameters more accurately within the selected frame or viewpoint. Thus, it would have been obvious to one skilled in the art prior to the effective filing date of the claimed invention to have combined the teachings of JP-5698815-B2 and Amano et. al. to have included the 3D shape information as training data for the object recognition device.
Regarding claim 8, JP-5698815-B2 discloses the object recognition device according to claim 1. However, JP-5698815-B2 fails to disclose wherein the three- dimensional shape approximation determination unit estimates a position of the predetermined rectangular region in the first image and determines whether to approximate to the predetermined three-dimensional shape information using a training device trained by using a second image including a general object approximatable to the predetermined three-dimensional shape information, information indicating a rectangular region including the general object in the second image, and the predetermined three-dimensional shape information as training data.
Amano et. al. discloses wherein the three- dimensional shape approximation determination unit estimates a position of the predetermined rectangular region in the first image and determines whether to approximate to the predetermined three-dimensional shape information using a training device trained by using a second image including a general object approximatable to the predetermined three-dimensional shape information, information indicating a rectangular region including the general object in the second image, and the predetermined three-dimensional shape information as training data ([0032] and Figure 10, the matching process involves the image processing device 30 first matching the feature points of P of two-dimensional image Ga extracted in S410 with the feature points Pm of three-dimensional shape model M, and shown in an excerpt below).
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Each feature of the target object requires a precise location that is identifiable as described by Amano et. al. so that the 3D information is reproducible as a 2D image. Thus, it would have been obvious to one skilled in the area prior to the effective filing date of the claimed invention to have combined the rectangular region of interest described in Amano et. al. with the object detection device of JP-5698815-B2.
Regarding claim 9 and 16, JP-5698815-B2 discloses the object recognition device according to claim 7 or 8. However, JP-5698815-B2 fail to disclose wherein the training data includes the second image which is an image obtained by capturing a 3D model having a size randomly selected from a certain range based on predetermined three-dimensional shape information and arranged in a virtual environment in a random position and posture by a virtual camera which is arranged in a position and posture in which an image of a surface of the 3D model is obtainable; information indicating a rectangular region including the 3D model; and the predetermined three-dimensional shape information.
However, Amano et. al. teaches wherein the training data includes the second image which is an image obtained by capturing a 3D model having a size randomly selected from a certain range based on predetermined three-dimensional shape information and arranged in a virtual environment in a random position and posture by a virtual camera which is arranged in a position and posture in which an image of a surface of the 3D model is obtainable; information indicating a rectangular region including the 3D model; and the predetermined three-dimensional shape information. (Amano et. al. Figure 2-3, three-dimensional model creation and Figure 5, [0027] various viewpoints of the workpiece shown).
The 3D model is essentially a virtual environment as described by the claimed invention and this is also disclosed in Amano et. al. This enables a more robust training dataset for the 3D information extraction to be carried out. Thus, it would have been obvious to one skilled in the art prior to the effective filing date of the claimed invention to have combined the teachings of JP-5698815-B2 with the teachings of Amano et. al. so that the objection recognition device can utilize a 3D model to extract 3D image information for the training data.
Allowable Subject Matter
Claims 10-15 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The prior art of record fail to anticipate the limitations of claims recited as cited in claims 10-15. None of the documents cited in the prior art of record or the international search report indicates that a first estimation region is extracted on the basis of a result of determination as to whether the region can be approximated to prescribed 3D shape information in addition to the first estimation region having a minimum area selected based on a rectangular bounding box.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JESSICA YIFANG LIN whose telephone number is (571)272-6435. The examiner can normally be reached M-F 7:00am-6:15pm, with optional day off.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vu Le can be reached at 571-272-7332. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JESSICA YIFANG LIN/Examiner, Art Unit 2668 January 22, 2026
/VU LE/Supervisory Patent Examiner, Art Unit 2668