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 .
Response to Amendment
The Amendments filed on December 31st, 2025 have been entered and made of record. By these amendments, claims 1-3 and 5 were amended and claim 4 has been cancelled. Additionally, claims 6-13 have been newly added. Claims 1-3 and 5-13 remain pending and rejected. Furthermore, applicant’s amendments to the specifications and claims have overcome each and every objection previously set forth in the Non-Final Office Action mailed October 17th, 2025 and have therefore been withdrawn.
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.
Claims 1 and 5-11 are rejected under 35 U.S.C. 103 as being unpatentable over Tomaru et al. (Pub. No.: US 2023/0260209 A1), hereinafter Tomaru, in view of Baron et al. (U.S. Patent: #11,024,065 B1), hereinafter Baron, and further in view of Hwang et al. (Pub. No.: US 2024/0193845 A1), hereinafter Hwang.
Regarding claim 1, Tomaru discloses a training data generation system comprising a processor (FIG. 7A and paragraph 97 teach that as illustrated in FIG. 7A, the training data generation device 100 is configured by a computer, and the computer has a processor 201 and a memory 202.) configured to:
acquire computer-aided design data containing a shape of an object (Paragraph 27 teaches that the learning device 20 acquires training data and performs machine learning for inferring a shape, a center position, a type, or the like of an object using the acquired training data. Specifically, the learning device 20 acquires the training data output from the training data generation device 100 from the training data generation device 100 or the storage device 10 to perform the machine learning.);
generate a three-dimensional model of the object recorded in the acquired computer-aided design data (Paragraph 72 teaches that specifically, every time the rendering condition acquiring unit 140 acquires each of a plurality of pieces of mutually different rendering condition information, the two-dimensional image acquiring unit 150 acquires two-dimensional image information indicating a two-dimensional image by rendering the 3D model with texture on the basis of the rendering condition information acquired by the rendering condition acquiring unit 140. Additionally, paragraph 76 teaches that the learning device 20 acquires the two-dimensional image information output by the training data output unit 190 as training data, performs machine learning using the acquired training data, and generates a trained model for inferring the shape, center position, type, or the like of the object.);
set an image generation condition for a simulation image of the object (Paragraph 64 teaches for example, the rendering condition acquiring unit 140 acquires the rendering condition information by reading out the rendering condition information from the storage device 10 in which the rendering condition information is stored in advance and paragraph 66 teaches that more specifically, for example, the rendering condition acquiring unit 140 acquires, as the rendering condition information, information indicating the position or attitude in a CG space of the 3D model indicated by the 3D model information acquired by the 3D model acquiring unit 110, the size of the 3D model including the bounding box in the CG space, the position or attitude of the virtual camera in the CG space, the position of the light source in the CG space, the color of the light emitted by the light source, or the like.);
add texture to the object in the simulation image based on the image generation condition (Paragraph 61 teaches that on the basis of the two-dimensional texture coordinates acquired by the texture coordinate acquiring unit 130, the rendering condition acquiring unit 140 acquires rendering condition information indicating a rendering condition that is a condition for rendering a 3D model with texture obtained by texture-mapping a partial image indicated by the partial image information on a 3D model indicated by the 3D model information.). However, Tomaru fails to disclose generate a shadow of the three-dimensional model of the object.
Baron discloses generate a shadow of the three-dimensional model of the object (FIG. 23 and Col. 25, Lines 20-33 teach that Step 2234 is optionally requested by the user by setting a software switch with values: “no shadow”, “original shadow (if available)”, or “synthesized shadow”. When “no shadow” is requested, no image processing occurs in step 2234. When “original shadow (if available)” is requested, the shadow image, if any, extracted in step 2218 is processed in the same manner as the object image was processed in steps 2222 and 2232, and then merged with the object image as a variably transparent darkened area. When “synthesized shadow” is requested, the object image is analyzed in conjunction with the processed positions of the vertices of the enclosing rectangular cuboid, and a variably transparent darkened area is applied to the region juxtaposed to the bottom of the object as so defined.). Since Tomaru teaches a training data generation system for utilizing computer-aided design training data to assist in generating three-dimensional models and Baron teaches a three-dimensional computer-aided design system for assisting in generating three-dimensional models, it would have been obvious to a person having ordinary skill in the art to combine the features together so that additionally, when generating three-dimensional models, shadows for the corresponding three-dimensional model could be generating and incorporated into the model generating process as well.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tomaru to incorporate the teachings of Baron, so that the combined functions together would allow for shadows to be generated alongside the three-dimensional models which would help improve the overall look and appearance of the model by being able to generate the three-dimensional models with realistic looking shadow effects.
Furthermore, Tomaru in view of Baron disclose convert the three-dimensional model to the image of the object and position information of the object in the image based on the computer-aided design data and the image generation condition, the image being a two-dimensional image (Paragraph 90 of Tomaru teaches that with the above-described configuration, the training data generation device 100 can output a plurality of information sets in which two-dimensional image information based on one piece of partial image information and label information are associated with each other on the basis of partial image information indicating a partial image that is an image area in which an object appears in a photographed image obtained by photographing the object and paragraph 138 teaches that furthermore, as described above, in the above-described configuration, the training data generation device 100 is configured so that the rendering condition acquiring unit 140 acquires, as the rendering condition information, information indicating at least one of the position and attitude of the 3D model in the CG space and the size of the 3D model. Lastly, paragraph 77 of Tomaru teaches that with the above-described configuration, the training data generation device 100 can output a plurality of pieces of two-dimensional image information based on one piece of partial image information on the basis of partial image information indicating a partial image that is an image area in which an object appears in a photographed image obtained by photographing an object.). However, Tomaru fails to disclose that the image is a simulation image.
Hwang discloses a simulation image (Paragraph 60 teaches that in other words, the rendered image simulator 260 may receive a real image stored in the training image database 210 and convert the real image into an image which simulates the unrealism of a three-dimensional (3D) graphic rendering image, thereby generating a rendering simulation image.). Since Tomaru in view of Baron teach an image generation unit (training data generation device) that can generate an image of an object and position information/conditions for that object (using rendering condition acquiring unit) to be used for training purposes and Hwang teaches a function for generating a simulation image to be used for training purposes, it would have been obvious to a person having ordinary skill in the art to combine the features together so that in addition to generating images for training purposes, a generated simulation image could also be included and implemented into the training process as well.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tomaru in view of Baron to incorporate the teachings of Hwang, so that the combined functions together would allow for additional training images to be used for training purposes, including those that involve any type of simulated images.
Furthermore, Tomaru in view of Baron and Hwang disclose and add the position information to the simulation image as annotation information and output the simulation image (Paragraph 84 of Tomaru teaches that in a case where the training data generation device 100 includes the label acquiring unit 160, the training data output unit 190 outputs the label information acquired by the label acquiring unit 160 in association with the two-dimensional image information, in addition to the two-dimensional image information indicated by the two-dimensional image acquiring unit 150 and paragraph 55 of Hwang teaches that the processor may perform an operation S301 of receiving training image data including a real image and an operation S303 of generating a rendering simulation image using the training image data).
Regarding claim 5, the method steps correspond to and are rejected similarly to the system steps of claim 1 (see claim 1 above).
Regarding claim 6, Tomaru in view of Baron and Hwang disclose everything claimed as applied above (see claim 1 above), in addition, Tomaru in view of Baron and Hwang disclose wherein the processor is further configured to:
set a depiction position and depiction angle of the object in the simulation image (Paragraph 69 of Tomaru teaches that for example, the rendering condition acquiring unit 140 acquires a rendering condition by reading out, from the storage device 10, information indicating a formula capable of determining the rendering condition such as the position or attitude (aka. angle) in the CG space of the 3D model indicated by the 3D model information acquired by the 3D model acquiring unit 110, the size of the 3D model including the bounding box in the CG space, the position or attitude (aka. angle) of the virtual camera in the CG space, or the position of the light source in the CG space or the color of the light emitted by the light source.);
and set a background of the simulation image of the object (Paragraph 162 of Tomaru teaches that the rendering condition acquiring unit 140 acquires rendering condition information indicating a rendering condition that is a condition for rendering the 3D model with texture corresponding to the object to be inferred and the 3D model with background texture corresponding to the background of the object together. Additionally, paragraph 163 teaches that on the basis of the rendering condition information acquired by the rendering condition acquiring unit 140, the two-dimensional image acquiring unit 150 acquires two-dimensional image information indicating a two-dimensional image by rendering the 3D model with texture corresponding to the object to be inferred and the 3D model with background texture corresponding to the background of the object together.).
Regarding claim 7, Tomaru in view of Baron and Hwang disclose everything claimed as applied above (see claim 1 above), in addition, Tomaru in view of Baron and Hwang disclose wherein the processor is further configured to define position coordinates of a point on a xyz coordinate space where the three-dimensional model of the object is generated (FIG. 1A and Col. 6, Lines 42-45 of Baron teach that FIG. 1A shows a three dimensional Cartesian coordinate system, 50, with orthogonal X, Y, and Z axes. A point in space is defined by the values of the X, Y, and Z coordinates as referenced to the origin, O.).
Regarding claim 8, Tomaru in view of Baron and Hwang disclose everything claimed as applied above (see claim 1 above), in addition, Tomaru in view of Baron and Hwang disclose wherein the processor is further configured to set position coordinates determined by the image generation condition for each simulation image (Col. 6, Lines 59-62 of Baron teaches that the three dimensional Cartesian coordinate system, 50, is used to define the position of points in physical space and FIG. 10 and Col. 13, Lines 45-53 of Baron teach that it can be seen in FIG. 10 that a class 1S1T image, 1010, can be made equivalent to a class 1S1 S rectangular cuboid image, 1030, by rotating the image by 90 degrees, 1015, using mathematical coordinate transformation methods known to those skilled in the art. FIG. 10 also shows that a class 1S1B image, 1020, can be made equivalent to a class 1S1 S rectangular cuboid image, 1030, by rotating the image by 90 degrees, 1025. The direction of rotation can be either clockwise or counterclockwise.).
Regarding claim 9, Tomaru in view of Baron and Hwang disclose everything claimed as applied above (see claim 1 above), in addition, Tomaru in view of Baron and Hwang disclose wherein the processor is further configured to perform blur processing on the simulation image (Paragraph 61 of Hwang teaches that for example, the rendered image simulator 260 may degrade the image quality of the received real image through image processing, such as color distortion, adding Gaussian noise, image resolution degradation, etc., thereby generating a rendering simulation image.).
Regarding claim 10, Tomaru in view of Baron and Hwang disclose everything claimed as applied above (see claim 1 above), in addition, Tomaru in view of Baron and Hwang disclose wherein the processor is further configured to perform image quality conversion processing on the simulation image (Paragraph 72 of Hwang teaches that likewise, the multi-resolution image converter 270 performs scaling on a real image in the training image database 210 using image interpolation. For example, an image may be generated by reducing horizontal and vertical sizes of the real image to ½, ¼, ⅛, etc. through the scaling and paragraph 73 teaches that according to the present invention, feature data corresponding to various image scales may be generated through scaling and used in training and inference.).
Regarding claim 11, Tomaru in view of Baron and Hwang disclose everything claimed as applied above (see claim 1 above), in addition, Tomaru in view of Baron and Hwang disclose wherein the three-dimensional model is a solid model (FIG. 3 and paragraph 40 of Tomaru teach that FIG. 3 is an explanatory diagram illustrating an example of a 3D model indicated by 3D model information acquired by the 3D model acquiring unit 110 included in the training data generation device 100 according to the first embodiment. Additionally, paragraph 41 teaches that specifically, FIG. 3 is obtained by visualizing the 3D model indicated by the 3D model information acquired by the 3D model acquiring unit 110 as a two-dimensional image by computer graphics (Hereinafter, referred to as “CG”.).).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Tomaru in view of Baron and Hwang as applied to claim 1 above, and further in view of Zhao et al. (Pub. No.: CN 111243058 A), hereinafter Zhao.
Regarding claim 2, Tomaru in view of Baron and Hwang disclose everything claimed as applied above (see claim 1), however, Tomaru in view of Baron and Hwang fail to disclose wherein the processor is further configured to output position information of an outline of the object in the simulation image as the position information of the object.
Zhao discloses wherein the processor is further configured to output position information of an outline of the object in the simulation image as the position information of the object (Paragraph 23 teaches that in one embodiment, the image features include at least two of the following: contour, shape, area, color, grayscale, brightness, saturation, and texture; the multiple simulation parameters include at least two of the following: starting pixel position, total number of generated pixels, color value, color difference, grayscale difference, grayscale value, saturation, saturation difference, brightness, brightness difference, texture, generation direction, generation shape, and generation position range. Additionally, paragraph 97 teaches that the simulation parameters of the simulated object can be selected according to the image features that the simulated object needs to have, such as the overall area, outline, shape, color, grayscale, saturation, brightness, texture, etc. of the simulated object. Simulation parameters can also be selected based on information that may be needed during the simulation generation process, such as the starting pixel position, the total number of generated pixels, color value, color difference, grayscale difference, grayscale value, saturation, saturation difference, brightness, brightness difference, texture, generation direction, generation shape, generation position range, etc. The selection range of simulation parameters can be set according to the image characteristics of the simulated object.). Since Tomaru in view of Baron and Hwang teach the initial generation steps that include using the positional information/conditions of objects in simulation images and Zhao teaches that a simulated object can include the positional contours and/or outlines of an object within an image, it would have been obvious to a person having ordinary skill in the art to combine the features together so that the positional information of an object within a simulation image could also take into account the outline positional information of that object as well.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tomaru in view of Baron and Hwang to incorporate the teachings of Zhao, so that the combined functions together would allow for more accurate object positioning within a simulation image by taking into account the outline parameters of the simulated object.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Tomaru in view of Baron and Hwang as applied to claim 1 above, and further in view of Meno (Pub. No.: US 2024/0212268 A1).
Regarding claim 3, Tomaru in view of Baron and Hwang disclose everything claimed as applied above (see claim 1), however, Tomaru in view of Baron and Hwang fail to disclose wherein the processor is further configured to set a depiction position of the object in the simulation image based on the image generation condition.
Meno discloses wherein the image generation unit is configured to set a depiction position of the object in the simulation image based on the image generation condition (Paragraph 70 teaches that the viewpoint information such as the position of the eye, the line of sight, the field of view, and the like acquired by the user information acquisition unit 24 is supplied to the determination unit 26 and the calculation unit 27. Additionally, paragraph 103 teaches that the calculation unit 27 calculates the amount of change in parallax of the tree 50 added to parallax calculation targets. When the amount of change in parallax is equal to or larger than a threshold, the display controller 28 switches the 3D-displayed tree 50 to be 2D-displayed. Further, the display controller 28 displays a 2D image of the tree 50 corresponding to the position (angle) as viewed from the user 51.). Since Tomaru in view of Baron and Hwang teach the initial generation steps that include using the positional information/conditions of objects in simulation images and Meno teaches an object positional configuration that takes into account viewpoint information, such as line of sight, so that an object can be displayed and depicted in the correct position for the viewer of the object, it would have been obvious to a person having ordinary skill in the art to combine the features together so that an object being displayed within a simulated image would then appear and look more proper with a fixed virtual viewpoint position.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tomaru in view of Baron and Hwang to incorporate the teachings of Meno, so that the combined functions together would provide a better and more accurate depiction of the object within the simulation image by taking into account the viewers perspective.
Claims 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Tomaru in view of Baron and Hwang as applied to claim 1 above, and further in view of Rapport et al (Pub. No.: US 2024/0127517 A1), hereinafter Rapport.
Regarding claim 12, Tomaru in view of Baron and Hwang disclose everything claimed as applied above (see claim 1), however, Tomaru in view of Baron and Hwang fail to disclose wherein the three-dimensional model is a surface model.
Rapport discloses wherein the three-dimensional model is a surface model (Paragraph 19 of Rapport teaches that in some embodiments, the product CAD models 110.1 through 110.n can include suitable three-dimensional product models, such as three-dimensional wireframe product models, three-dimensional polygonal product models, three-dimensional solid product models, and/or three-dimensional surface product models to provide some details, that can be viewed from any orientation and/or angle in three-dimensional space that will be apparent to those skilled in the relevant art(s) without departing from the spirit and the scope of the present disclosure.). Since Tomaru in view of Baron and Hwang teach utilizing computer-aided design data to help in training and generating three-dimensional models and Rapport teaches utilizing computer-aided design data that may consist of many different three-dimensional model designs, including a surface model type, it would have been obvious to a person having ordinary skill in the art to combine the features together so that a three-dimensional model would be able to consist of different types of models, including a surface model.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tomaru in view of Baron and Hwang to incorporate the teachings of Rapport, so that the combined functions together would allow a user to ability to take advantage of using more options when generating a three-dimensional model type, including the capability of generating a surface model type.
Regarding claim 13, Tomaru in view of Baron and Hwang disclose everything claimed as applied above (see claim 1), however, Tomaru in view of Baron and Hwang fail to disclose wherein the three-dimensional model is a wire frame model.
Rapport discloses wherein the three-dimensional model is a wire frame model (Paragraph 19 of Rapport teaches that in some embodiments, the product CAD models 110.1 through 110.n can include suitable three-dimensional product models, such as three-dimensional wireframe product models, three-dimensional polygonal product models, three-dimensional solid product models, and/or three-dimensional surface product models to provide some details, that can be viewed from any orientation and/or angle in three-dimensional space that will be apparent to those skilled in the relevant art(s) without departing from the spirit and the scope of the present disclosure.). Since Tomaru in view of Baron and Hwang teach utilizing computer-aided design data to help in training and generating three-dimensional models and Rapport teaches utilizing computer-aided design data that may consist of many different three-dimensional model designs, including a wire frame model type, it would have been obvious to a person having ordinary skill in the art to combine the features together so that a three-dimensional model would be able to consist of different types of models, including a wire frame model.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tomaru in view of Baron and Hwang to incorporate the teachings of Rapport, so that the combined functions together would allow a user to ability to take advantage of using more options when generating a three-dimensional model type, including the capability of generating a wire frame model type.
Response to Arguments
Applicant’s arguments with respect to independent claims 1 and 5 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. The prior art of Baron has been incorporated into the rejection of independent claims 1 and 5 and therefore teach the newly amended claim language, specifically in regards to teaching “a processor configured to ... generate a shadow of the three-dimensional model of the object” (see claims 1 and 5 above).
In regards to any additional arguments regarding the dependent claims 2 and 3 and any of the newly added claims 6-13, for the virtue of their dependency are moot because the independent claims are not allowable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Cook et al. (Pub. No.: US 2007/0115275 A1) teaches a method for manipulating the position and appearance of shadows of objects within a three-dimensional model.
Knorr et al. (U.S. Patent: #11,182,974 B2) teaches a method for representing a model of a real or virtual object by a CAD model and generate a virtual model with proper shadow generation effects.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/G.R./Examiner, Art Unit 2613
/XIAO M WU/Supervisory Patent Examiner, Art Unit 2613
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