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 .
Response to Amendment
The Amendment filed March 5, 2026 has been entered. Claims 1-12 remain pending in the application. Applicant’s amendments to the Claims have overcome each and every objection previously set forth in the Non-Final Office Action mailed December 15, 2025.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/23/2026 is in compliance with the provisions of 37 CFR 1.97 and has been considered by the examiner.
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.
Claim(s) 1-3, 5-8 and 10-12 are rejected under 35 U.S.C. 103 as being unpatentable over Beijing Wuyu Tech Co. LTD (CN111179408A), hereinafter referred to as CN '408, in view of Schiebener et al. (NPL “Heuristic 3D Object Shape Completion based on Symmetry and Scene Context”).
Regarding claim 1, CN ‘408 discloses a method for computer-implemented completion of a 3D partial model - formed by a point cloud - of a partial region of an object (paragraph 0123: “3D model of the initially known part includes a point cloud composed of feature points corresponding to the initially known part of the target object”) that is captured by at least one capture device (paragraph 0010: “Acquire images containing the target object captured in real time by an image acquisition device”), wherein the 3D partial model is configured to be supplemented with a hidden or missing partial region of the object situated outside the 3D partial model of the object that is to be completed (paragraph 0091: “the invisible portion of the target object in the image used for initial modeling is called the initial unknown portion”), comprising: a) determining a geometry of the object by: comparing the 3D partial model with one or more comparable 3D objects from a knowledge base of objects (paragraph 0012: “The three-dimensional model of the initially known part is matched with multiple models in the model library”) using a trained and trainable neural network (paragraph 0097: “matching is performed using artificial intelligence algorithms. That is, using known complete 3D models as samples to train the model library”), determining that comparing the 3D partial model with one or more comparable 3D objects from the knowledge base of objects was not successful or was only partly successful, wherein one or more partial areas of the 3D partial model are still missing or hidden (paragraph 0098: “if the 3D model of the initial known part does not match any of the other categories in the known model library” or “the matching result may be a failure”), and in response to determining that comparing the 3D partial model with one or more comparable 3D objects from the knowledge base of objects was not successful or was only partly successful, comparing the 3D partial model with a 3D model that arose as a result of mirroring at least one part of the 3D partial model (paragraph 0098: “The matching result of this category is symmetry matching, that is, the target object is considered a symmetric object, and the 3D model of the initial known part is transformed symmetrically to serve as the 3D model of its initial unknown part”); b) identifying the hidden or missing partial region of the object on the basis of the determined geometry of the object (paragraph 0012: “the three-dimensional model of the initially unknown part of the target object is determined based on the matching results”); c) supplementing the 3D partial model to form a complete 3D model with the identified hidden or missing partial region of the object (paragraphs 0022, 0099: “an initial complete three-dimensional model of the target object can be obtained further based on the three-dimensional model of the initially known part of the target object and the three-dimensional model of the initially unknown part” where “the three-dimensional model of the dynamic object includes the three-dimensional model of the initially known part and/or the three-dimensional model of the initially unknown part”); and d) outputting the completed 3D model at an output unit (paragraph 0031: “Obtain and output the complete 3D model of the target object”); wherein the method is repeated until a predefinable quality measure of completeness of the completed 3D model is attained (paragraph 0128: “Through repeated updates of values and data acquisition updates of the target object's zoomed-in parts, the accuracy of the target object's 3D model can be gradually improved”). However, CN ‘408 fails to explicitly disclose mirroring at least one part of the 3D partial model at a previously ascertained plane of symmetry or axis of symmetry. In the related art of 3D shape completion, Schiebener discloses mirroring at least one part of the 3D partial model at a previously ascertained plane of symmetry or axis of symmetry (Schiebener Fig. 1, page 75: “Once the best one [symmetry plane] has been determined, it is used to mirror the perceived points and thus obtain a back side for the object, i.e. the side of the object that is turned away from the camera”). 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 CN ‘408 to incorporate the teachings of Schiebener to choose the best symmetry plane for completing a surface with high plausibility (Schiebener page 77).
Regarding claim 2, CN ‘408, modified by Schiebener, discloses the method claimed in claim 1, wherein a 3D object recognition method is carried out, which searches through the knowledge base of objects for one or more comparable objects (CN ‘408 paragraph 0012: “The three-dimensional model of the initially known part is matched with multiple models in the model library”), wherein a set of recognized comparable objects is output as a result of the 3D object recognition (CN ‘408 paragraph 0098: “In one implementation, the matching result is the 3D model of the initial unknown part of the target object”).
Regarding claim 3, CN ‘408, modified by Schiebener, discloses the method claimed in claim 2, wherein the trained and trainable neural network is used to recognize a similarity between the 3D partial model and at least one 3D object from the knowledge base (CN ‘408 paragraph 0097: “matching is performed using artificial intelligence algorithms. That is, using known complete 3D models as samples to train the model library”).
Regarding claim 5, CN ‘408, modified by Schiebener, discloses the method claimed in claim 1, wherein the partial region of the object comprises only one side of the object (Schiebener Fig. 1, page 75: “only the front side of the object was perceived”).
Regarding claim 6, it is the corresponding apparatus configured to execute the method claimed in claim 1. Therefore, CN ‘408, modified by Schiebener, discloses the limitations of claim 6 as it does the limitations of claim 1.
Regarding claim 7, it is the corresponding apparatus configured to execute the method claimed in claim 2. Therefore, CN ‘408, modified by Schiebener, discloses the limitations of claim 7 as it does the limitations of claim 2.
Regarding claim 8, it is the corresponding apparatus configured to execute the method claimed in claim 3. Therefore, CN ‘408, modified by Schiebener, discloses the limitations of claim 8 as it does the limitations of claim 3.
Regarding claim 10, it is the corresponding apparatus configured to execute the method claimed in claim 5. Therefore, CN ‘408, modified by Schiebener, discloses the limitations of claim 10 as it does the limitations of claim 5.
Regarding claim 11, it is the corresponding computer program product configured to execute the method claimed in claim 1. Therefore, CN ‘408, modified by Schiebener, discloses the limitations of claim 11 as it does the limitations of claim 1.
Regarding claim 12, it is the corresponding computer program product configured to execute the method claimed in claim 1. Therefore, CN ‘408, modified by Schiebener, discloses the limitations of claim 12 as it does the limitations of claim 1.
Claim(s) 4 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over CN ‘408 and Schiebener in view of D'Ambrosio et al. (WO 2007/095284).
Regarding claim 4, CN ‘408, modified by Schiebener, discloses the method claimed in claim 1, wherein the plane of symmetry or the axis of symmetry is ascertained by displacing the plane of symmetry or axis of symmetry as perpendicularly as possible to a reference plane of the object (Schiebener page 76: “the symmetry plane of the object is perpendicular to the supporting surface”) step by step over the surface of the 3D partial model (Schiebener page 76: “we create symmetry plane candidates by uniform sampling…by rotating and shifting the [initial symmetry] plane over regular intervals”). However, CN ‘408 and Schiebener fail to disclose displacing the plane of symmetry or axis of symmetry until a comparison of partial regions of the 3D partial model on one side of the plane of symmetry or axis of symmetry with partial regions of the 3D partial model on the other side of the plane of symmetry or axis of symmetry attains a predefinable degree of correspondence. In the related art of automatic symmetry identification, D'Ambrosio discloses displacing the plane of symmetry or axis of symmetry (D'Ambrosio paragraph 0178: “searching over a set of possible planes”) until a comparison of partial regions of the 3D partial model on one side of the plane of symmetry or axis of symmetry with partial regions of the 3D partial model on the other side of the plane of symmetry or axis of symmetry attains a predefinable degree of correspondence (D'Ambrosio paragraph 0178: “a method to automatically compute the symmetry plane and correct the 3D orientation of patient brain images. Similar to most existing 3D approaches, the midsagittal plane is defined as the one that maximizes the similarity between two halves of the brain”). 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 CN ‘408 and Schiebener to incorporate the teachings of D'Ambrosio to determine the plane of symmetry in a way that is insensitive to acquisition noise, bias field and pathological asymmetries and the incomplete field of view (D'Ambrosio paragraph 0181).
Regarding claim 9, it is the corresponding apparatus configured to execute the method claimed in claim 4. Therefore, CN ‘408, modified by Schiebener and D'Ambrosio, discloses the limitations of claim 9 as it does the limitations of claim 4.
Response to Arguments
Applicant's arguments have been fully considered but they are not persuasive.
Regarding the argument that “This iterative repetition of the recited steps does not rely on acquiring new image data and is distinct from the cited reference's tracking-based approach that depends on acquiring new views and additional data of the object”, it is noted that the features upon which applicant relies (i.e., “This iterative repetition of the recited steps does not rely on acquiring new image data”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Claim 1 does not require the iterative repetition of the method to exclude acquiring new image data. CN ‘408 teaches repeatedly updating values of the unknown parts of the target object to improve the 3D model accuracy without exceeding the maximum required accuracy (CN ‘408 paragraphs 0128 and 0130). Thus, CN ‘408 teaches repeating the steps of the method until a required accuracy of the completed 3D model is attained.
Regarding the argument that “CN ‘408 teaches its own solution for completing the model and does not rely on mirroring as contemplated by the claimed embodiments”, CN ‘408 teaches if the 3D model of the initial known part does not match any of the other categories in the known model library or the matching result may be a failure, the 3D model of the initially known part is transformed symmetrically to serve as the 3D model of its initially unknown part. (CN ‘408 paragraph 0098). Therefore, CN ‘408 does rely on mirroring for completing the 3D model.
Regarding the argument that “There is no reason (apart from having the benefit of Applicant's own disclosure) why one of skill in the art would be motivated to apply the symmetry-based process of Schiebener to the primary reference” and the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971). As discussed above, CN ‘408 teaches mirroring the 3D model of the initially known part. Schiebener teaches determining the best symmetry plane for mirroring the perceived points. The combined teachings of CN ‘408 and Schiebener would have suggested to those of ordinary skill in the art at the time that the 3D partial model can be mirrored at a previously determined symmetry plane. One of ordinary skill in the art would be motivated to apply Schiebener’s selection of the best symmetry plane to CN ‘408’s mirroring of the 3D partial model to increase the plausibility of the completed 3D model (as delineated in the above rejection).
Conclusion
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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/C.Z./Examiner, Art Unit 2677
/ANDREW W BEE/Supervisory Patent Examiner, Art Unit 2677
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