Office Action Predictor
Application No. 17/988,783

ENCODING METHOD, DECODING METHOD, AND DEVICE FOR POINT CLOUD COMPRESSION

Non-Final OA §103
Filed
Nov 17, 2022
Examiner
LU, ZHIYU
Art Unit
2665
Tech Center
2600 — Communications
Assignee
Industrial Technology Research Institute
OA Round
1 (Non-Final)
49%
Grant Probability
Moderate
1-2
OA Rounds
3y 8m
To Grant
64%
With Interview

Examiner Intelligence

49%
Career Allow Rate
372 granted / 757 resolved
Without
With
+15.2%
Interview Lift
avg trend
3y 8m
Avg Prosecution
58 pending
815
Total Applications
career history

Statute-Specific Performance

§101
2.9%
-37.1% vs TC avg
§103
66.5%
+26.5% vs TC avg
§102
11.9%
-28.1% vs TC avg
§112
17.0%
-23.0% vs TC avg
Black line = Tech Center average estimate • Based on career data

Office Action

§103
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 . Election/Restrictions Applicant’s election without traverse of claims 12-14 in the reply filed on 07/04/2025 is acknowledged. 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. Claim(s) 12-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pham Van et al. (US2024/0251097) in view of Huang et al. (CN109727312). To claim 12, Pham Van teach a decoding method for point cloud compression (paragraph 0030), comprising: obtaining a bitstream (paragraphs 0013, 0016-0017), wherein the bitstream comprises reference point cloud data corresponding to a reference frame (paragraph 0061, reference cloud), a global point cloud set corresponding to a first frame, a global dynamic model corresponding to the global point cloud set (paragraphs 0062, 0073, entropy decode data representing a global motion vector for a current point cloud of the series of frames), a serial number (paragraphs 0174-0184, slice number/identifier; paragraph 0139, object label, wherein serial number would be an obvious implementation) of at least one object point cloud set in at least one reference object point cloud set (paragraphs 0027-0028, points in point clouds corresponding to the objects can be predicted using a common, global motion vector; paragraphs 0056, 0062, 0258, coding the object points comprises applying the rotation matrix and the translation vector to reference points of a reference frame), and at least one object dynamic model corresponding to the at least one object point cloud set (paragraph 0045, dynamic point cloud; paragraph 0165, dynamic slice group), wherein the reference point cloud data comprises the at least one reference object point cloud set (paragraphs 0257-0258); and reconstructing first point cloud data corresponding to the first frame according to the reference point cloud data, the global point cloud set corresponding to the first frame, the global dynamic model, the serial number of the at least one object point cloud set in the at least one reference object point cloud set, and the corresponding at least one object dynamic model (paragraphs 0049, 0057, 0064-0065, 0075, 0240-0245). In furthering said obviousness, Huang teach object in a frame of point cloud data including size information, direction information, a type and serial number of said object (paragraph 0009). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Huang into the method of Pham Van, in order to further detail in identifying object in point cloud. To claim 13, Pham Van and Huang teach claim 12. Pham Van and Huang teach wherein a global motion vector in the global dynamic model comprises a global translation vector and a global rotation vector (Pham Van, paragraphs 0045, 0121, 0157), and reconstructing the first point cloud data corresponding to the first frame comprises: obtaining a plurality of global points from the reference point cloud data according to the global point cloud set, producing a global point product after multiplying each of the global points by the global rotation vector, and adding the global translation vector to the global point product to form global point cloud information (paragraphs 0121, 0129, 0140, 0157, 0257, 0299, 0345, 0371, 0384, 0410, applying the rotation matrix and the translation vector to reference points of a reference frame; despite lack of teaching on the applying, multiplying rotation vector and adding translation vector are well-known in the art, which would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate for implementation, hence Official Notice is taken). To claim 14, Pham Van and Huang teach claim 13. Pham Van and Huang teach wherein an object motion vector in the object dynamic model comprises an object translation vector and an object rotation vector, and reconstructing the first point cloud data corresponding to the first frame further comprises: for each of the object point cloud set corresponding to the first frame, obtaining a plurality of object points from the reference point cloud data according to the serial number in the at least one reference object point cloud set, producing an object point product after multiplying each of the object points by the object rotation vector, and adding the object translation vector to the object point product to form at least one object point cloud information; and combining the global point cloud information and the at least one object point cloud information into the first point cloud data (Pham Van, paragraph 0207, motion parameters for a reference frame may be specified in terms of regions, whereas one or more slice groups may be specified for the current frame; a slice group may be associated with a region (explicitly or implicitly) and reference points from region may be used to predict points of the slice group; Huang, paragraph 0061, different objects are labeled to different numbers; wherein Pham Van and Huang obviously teach said reconstruction of frame with object dynamic model, Official Notice is also taken). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHIYU LU whose telephone number is (571)272-2837. The examiner can normally be reached Weekdays: 8:30AM - 5:00PM. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen R Koziol can be reached at (408) 918-7630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. ZHIYU . LU Primary Examiner Art Unit 2669 /ZHIYU LU/Primary Examiner, Art Unit 2665 September 9, 2025
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Prosecution Timeline

Nov 17, 2022
Application Filed
Sep 09, 2025
Non-Final Rejection — §103
Apr 06, 2026
Response after Non-Final Action

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Prosecution Projections

1-2
Expected OA Rounds
49%
Grant Probability
64%
With Interview (+15.2%)
3y 8m
Median Time to Grant
Low
PTA Risk
Based on 757 resolved cases by this examiner