Prosecution Insights
Last updated: April 19, 2026
Application No. 18/036,644

POINT CLOUD DATA TRANSMISSION METHOD, POINT CLOUD DATA TRANSMISSION DEVICE, POINT CLOUD DATA RECEPTION METHOD, AND POINT CLOUD DATA RECEPTION DEVICE

Non-Final OA §103
Filed
May 11, 2023
Examiner
GUILLERMETY, JUAN M
Art Unit
2682
Tech Center
2600 — Communications
Assignee
LG Electronics Inc.
OA Round
3 (Non-Final)
72%
Grant Probability
Favorable
3-4
OA Rounds
2y 5m
To Grant
83%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allow Rate
430 granted / 597 resolved
+10.0% vs TC avg
Moderate +11% lift
Without
With
+10.8%
Interview Lift
resolved cases with interview
Typical timeline
2y 5m
Avg Prosecution
27 currently pending
Career history
624
Total Applications
across all art units

Statute-Specific Performance

§101
6.4%
-33.6% vs TC avg
§103
60.4%
+20.4% vs TC avg
§102
21.9%
-18.1% vs TC avg
§112
7.1%
-32.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 597 resolved cases

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 . In a RCE and amendments dated 12/23/2025, applicants amended claims 1, 3, 4, 6, 7, 9, 10, 12, 13, 16 and 18 – 21. Claims 1 – 22 are still pending in this application. Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/23/2025 has been entered. Response to Arguments Applicant’s arguments with respect to claims 1 - 22 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. 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. 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. Claims 1 - 22 are rejected under 35 U.S.C. 103 as being unpatentable over Kang et al. (U.S PreGrant Publication No. 2018/032279 A1, hereinafter ‘Kang’) in view of Hur et al. (U.S PreGrant Publication No. 2021/0211722 A1, hereinafter ‘Hur’). With respect to claim 1, Kang teaches a method (e.g., a method, ¶0010) of transmitting point cloud data, the method comprising: encoding geometry data in a slice based on a tree (e.g., encoding geometry data in a slice based on a tree structure, ¶0079, ¶0113 with ¶0152); and encoding attribute data in the slice (e.g., encoding slice information, ¶0127), wherein the encoding the geometry data in the slice includes: generating a quantization parameter (e.g., generating a quantization parameter, ¶0103, ¶0122 - ¶0123); generating a slice quantization parameter (e.g., generating a slice header, ¶0087, ¶0343, ¶0349, ¶0352); generating a quantization parameter offset related to a node of the tree based on the slice quantization parameter and the quantization parameter (e.g., generating an offset related to a unit of the tree structure based on slice header and quantization parameter, ¶0096, ¶0118, ¶0133); obtaining scaled residual geometry data based on the quantization parameter (e.g., scaled residual geometry data based on quantization parameter is obtained, ¶0024, ¶0089, ¶101 - ¶0103, ¶0240,); generating predictive geometry data based on inter prediction (e.g., generating predicted geometry data based on inter prediction, abstract, ¶0129, ¶0236 - ¶0238, ¶0254, ¶0308, Fig. 32); and reconstructing the geometry data based on the scaled residual geometry data and the predictive geometry data (e.g., reconstructing the geometry data based on the scaled/residual geometry data and the predicted geometry data, ¶0024, ¶0130 - ¶0131, ¶0139 - ¶0142, ¶0289); but fails to teach that said encoded geometry data is of point cloud data based on the tree including a node; and that said attribute data of the point cloud data is encoded based on Levels of Detail (LoD), wherein the geometry data represents data of position of points for the point cloud data; and the aforementioned sequence is performed for the node. However, in the same field of endeavor of encoding geometry data and attribute data for point cloud data, Hur teaches: encoding geometry data in a slice of a point cloud data based on a tree including a node (e.g., encoding geometry data of a point cloud data (¶0341) based on an octree that includes at least a current node or current point, ¶0066, ¶0341 - ¶0342, ¶0423, Claim 12, Fig. 15, Fig. 22 & Fig. 34); encoding attribute data based on LoDs (e.g., encoding attribute based on LoDS, ¶0288, ¶0385); where the geometry data represents data of positions of point for the point cloud data (e.g., said geometry data can contains position of points for a point cloud data, ¶00066); and a sequence is performed for the node (e.g., Hur discloses encoding geometry data and attribute data based on the LoDs; quantizing; obtaining residual geometry data; predict geometry data, and reconstruct geometry data for each node or point; however, that sequence is started with a first node as an original node before dividing, ¶0121, ¶0280, ¶0400, ¶0516, Fig. 4, Fig. 22). Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the method of Kang as taught by Hur since Hur suggested within ¶0288, ¶0385, ¶0400, ¶0516 and Fig. 22 that such modification would increase compression efficiency for the node in order to reduce amount of computation. With respect to claim 2, Kang in view of Hur teaches the method of claim 1, wherein the encoded geometry data and the encoded attribute data are included in a bitstream, and wherein the bitstream further includes information representing splitting the node into quantization subnodes, each of which corresponds to a unit of the quantization parameter offset (e.g., the bitstream should contains information in order to divide a unit into sub-units, and related to the offset, ¶0083, ¶088 - ¶0090, ¶0096, ¶0118, ¶0185, ¶0133, ¶0216 - ¶0217). With respect to claim 3, Kang in view of Hur teaches the method of claim 1, wherein the encoding the geometry data in the slice further includes: selecting the predictive geometry data by deleting at least one of the predictive geometry data; and generating residual geometry data based on original geometry data and the selected predictive geometry data (e.g., selecting the predicted geometry by putting aside (disregard) at least one of the predicted geometric data; and generating residual geometry based on original geometry and the selected predicted geometry, ¶0011 - ¶0012, ¶180, ¶0185, ¶0309 and ¶0327); and Hur teaches for the node (e.g., generating residual geometry data from the original node, ¶0132 - ¶0133, ¶0354, ¶0377 - ¶0380, ¶0408). With respect to claim 4, Kang in view of Hur teaches the method of claim 1, wherein the obtaining the scaled residual geometry data includes: obtaining transform coefficients by inverse-quantizing a quantized residual geometry data based on the quantization parameter and obtaining the scaled residual geometry data by inverse-transforming the transform coefficients (e.g., the information on the geometric modification information may include residual geometric modification information or a scaling coefficient, and at the reconstructing the geometric modification information may be performed based on at least one of the residual geometric modification information and the scaling coefficient, and previously stored geometric modification information, ¶0024, ¶0101 - ¶0103); and Hur teaches for the node (e.g., involving inverse-transforming using coefficients, ¶0132 - ¶0138, ¶0150, ¶0159, ¶0401, ¶0409, Fig. 4 & Fig. 11). With respect to claim 5, Kang in view of Hur teaches the method of claim 4, wherein the inverse-transforming is performed per a transform unit, and wherein the one or more transform units constitute a quantization unit (e.g., refer to ¶0114). With respect to claim 6, Kang in view of Hur teaches the method of claim 1, wherein the encoding the geometry data in the slice further includes: generating predicted occupancy based on predictive geometry data (e.g., generating a first prediction block of a current block by performing inter prediction referencing the geometric modified picture, abstract, ¶0010); generating original occupancy based on original geometry data (e.g., generating original block based on original image, Fig. 15, ¶0195); and generating residual occupancy based on the original occupancy and the predicted occupancy (e.g., generating residual block based on original and prediction block, ¶0128)); and Hur teaches for the node (Fig. 13). With respect to claims 7 - 12, these are apparatus claims corresponding to the method claims 1—- 6, respectively. Therefore, these are rejected for the same reasons as the method claim 1-6, respectively. With respect to claim 13 - 17, these are method claims corresponding to the apparatus claims 1 – 5, respectively. Therefore, this is rejected for the same reasons as the apparatus claims 1 – 5, respectively. With respect to claims 18 - 19, these are apparatus claims corresponding to the method claims 13 and 14, respectively. Therefore, these are rejected for the same reasons as the method claims 13 and 14, respectively. With respect to claim 20, it's rejected for the similar reasons as those described in connection with claim 3. With respect to claims 21 - 22, these are rejected for the similar reasons as those described in connection with claim 16 and 17, respectively. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to JUAN M GUILLERMETY whose telephone number is (571)270-3481. The examiner can normally be reached 9:00AM - 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, Benny Q TIEU can be reached at 571-272-7490. 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. /JUAN M GUILLERMETY/Primary Examiner, Art Unit 2682
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Prosecution Timeline

May 11, 2023
Application Filed
May 22, 2025
Non-Final Rejection — §103
Aug 25, 2025
Response Filed
Oct 01, 2025
Final Rejection — §103
Dec 23, 2025
Request for Continued Examination
Jan 14, 2026
Response after Non-Final Action
Feb 05, 2026
Non-Final Rejection — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
72%
Grant Probability
83%
With Interview (+10.8%)
2y 5m
Median Time to Grant
High
PTA Risk
Based on 597 resolved cases by this examiner. Grant probability derived from career allow rate.

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