DETAILED ACTION
Status
This Office Action is responsive to claims filed on 09/05/2024. Please note Claims 8-13 are pending and have been examined.
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) submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claim 8 is objected to because of the following informalities: “a deviation between the first input image data and and the second output image data” should be “a deviation between the first input image data and
Claims 8-11 recite “2D” and “3D” multiple times. Applicant is suggested to clarify whether these terms correspond to “two-dimensional” and “three-dimensional”, respectively.
Claim 12 and Claim 13 recite similar features of claim 8. Appropriate corrections are required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 8-13 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 8 recites “the trainable ML model” which lacks antecedent basis. It’s unclear whether “the trainable ML model” refers to the machine learning model in the preamble of this claim. Applicant is suggested to use consistent terminology when referring to a same limitation.
Claim 8 recites “the generated 3D representation for the at least one voxel feature” which lacks antecedent basis. The claim merely recites generating a voxel-based 3D representation for the environment of the vehicle, but fails to disclose generating 3D representation for at least one voxel feature.
Claim 8 recites “the generated 3D representation of the ML model” which lacks antecedent basis. This feature possibly refers to the 3D representation generated by using the ML model, not a 3D representation of the ML model.
Claims 9-11 are dependent from claim 8 and are therefore rejected.
Claim 12 and Claim 13 recite similar features of claim 8, and are therefore rejected.
Allowable Subject Matter
Claims 8-13 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 8, Yi Wei (“SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving”, published in IEEE International Conference on Computer Vision, 3/16/2023) discloses a method to “extract multi-scale features for each image and adopt spatial 2D-3D attention to lift them to the 3D volume space” and “progressively upsample the volume features and impose supervision on multiple levels”.
In the same filed of endeavor, Horstmeyer (US 20230070475 A1) discloses “the fitting of the image representations into the volumetric representation can be accomplished by minimizing variations between the complex function representing the volumetric representation and the multiple complex functions representing the image representations”.
However, claim 8 recites “…comparing the first input image data with the generated second output image data; and based on determining a deviation between the first input image data and and the second output image data, adjusting at least one parameter of the ML model to minimize the ascertained deviation and thus train the ML model and thus improve the generated 3D representation of the ML model”. The combination of these features with other limitations as cited in the claim are neither disclosed nor suggested by the prior art of record.
Independent Claims 12 and 13 recite similar features of claim 8.
Conclusion
The following art is considered pertinent to applicant's disclosure:
Gigengack (US 20250022226 A1) corresponding to co-pending Application # 18766036 filed by the same inventor has been considered by the Examiner.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHONG WU whose telephone number is (571)270-5207. The examiner can normally be reached MON-FRI: 9AM-5PM EST.
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/CHONG WU/Primary Examiner, Art Unit 2613