Prosecution Insights
Last updated: April 19, 2026
Application No. 18/861,188

POINT CLOUD COMPRESSION METHOD AND APPARATUS

Final Rejection §103
Filed
Oct 28, 2024
Examiner
ZEWEDE, ASTEWAYE GETTU
Art Unit
2481
Tech Center
2400 — Computer Networks
Assignee
Intellectual Discovery Co. Ltd.
OA Round
2 (Final)
80%
Grant Probability
Favorable
3-4
OA Rounds
2y 7m
To Grant
99%
With Interview

Examiner Intelligence

Grants 80% — above average
80%
Career Allow Rate
36 granted / 45 resolved
+22.0% vs TC avg
Strong +38% interview lift
Without
With
+37.5%
Interview Lift
resolved cases with interview
Typical timeline
2y 7m
Avg Prosecution
18 currently pending
Career history
63
Total Applications
across all art units

Statute-Specific Performance

§101
0.7%
-39.3% vs TC avg
§103
67.0%
+27.0% vs TC avg
§102
10.4%
-29.6% vs TC avg
§112
10.4%
-29.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 45 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 . Priority Receipt is acknowledged of certified copies of papers submitted under 35 U.S.C. 119(a)- (d), which papers have been placed of record in the file. Status of Claims 2. This Office Action is in response to the amendment filed on 01/16/2026. Claims 1 and 11 have been amended. Claims 6-7 have been cancelled. Accordingly, claims 1-5 and 8-11 are currently pending for examination. Information Disclosure Statement 4. The information disclosure statement (IDS) submitted on 10/28/2024 filed in accordance with the provisions of 37 CFR 1.97. Accordingly, it is being considered by the examiner. Response Amendments 5. Applicant’s Amendment filed on January 16, 2026 has been entered and made of record. Claim interpretation 6. The Examiner notes that the limitation: “wherein the geometric information of the current point is determined based on at least one of the motion compensated point or a point included in a plane of at least one triangle,” is recited in the alternative. Accordingly, the limitation requires that the geometric information of the current point be determined based on at least one of (not all) the following limitation: the motion compensated point, the point included in the plane of the at least one triangle, or both the motion compensated point and the point included in the plane of the at least one triangle. Response to Arguments 7. Applicant’s arguments filed on 01/16/2026, (see Pages 6-10), with respect to claims 1 and 11 have been fully considered, but are not persuasive. Applicant argues that Cao, Flynn, and Zhang fail to disclose “wherein the geometric information of the current point is determined based on at least one of the motion compensated point or a point included in a plane of at least one triangle.” Applicant further contends that Flynn is silent with respect to “motion compensated data” and therefore does not teach the limitation. The Examiner respectfully disagrees, As set forth in the claim interpretation, the limitation is recited in the alternative (at least one of… or …”). Accordingly, the limitation is satisfied if the geometric information of the current point is determined based on either (1) the motion compensated point or (2) a point included in a plane of at least one tringle. Cao discloses determining a locally motion compensated point corresponding to the current point by performing local motion compensation on the current predication unit (Cao ¶[0004], ¶[0083]). A motion compensated point necessarily has associated spatial coordinates (e.g., X, Y, Z). Thus, determining the motion compensated point inherently provides the geometric information (i.e., spatial position) corresponding to the current point. Accordingly, Cao teaches determining the geometric information of the current point based on the motion compensated point. Applicant’s argument that Flynn does not disclose motion compensated data is not persuasive because the rejection does not rely on Flynn for teaching the determination based on the motion compensated point. Rather, Cao provides the teaching of motion compensation, while Flynn is relied upon for teaching geometric representation of point cloud data, including representing positions of points in a volumetric space. Furthermore, because the limitation is written in the alternative, disclosure of determining the geometric information of the current point based on the motion compensated point alone is sufficient to meet the limitation. There is no requirement that both the motion compensated and the triangle-based determination be used. Therefore, Applicant’s arguments are not persuasives. Claim Rejections - 35 USC § 103 8. 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 9. Claims 1-5, and 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over CAO KEMING (WO-2022076701-A1) hereinafter “Cao” in view of Flynn et al (US-11741638-B2) hereinafter “Flynn”. Regarding Claim 1 Cao-Flynn Cao discloses 1. (Currently Amended) A method for compressing a point cloud, (Cao, claim 23 “A method for encoding point cloud data,”) comprising: performing global motion compensation based on a previous frame of a current frame; (Cao, [0004] “…apply “global” motion compensation to the reference frame (e.g., a predicted frame) to account for a rotation of the entire reference frame and/or a translation of the entire reference frame…”) dividing the current frame into a plurality of prediction units; (Cao, [0021] “A geometry-based point cloud compression (G-PCC) coder (e.g., a G-PCC encoder or a G-PCC decoder) may be configured to apply motion compensation to a reference frame to generate a motion compensated frame. For example, a G-PCC encoder may apply “global” motion compensation to the reference frame to account for a rotation of the entire reference frame and/or a translation of the entire reference frame.” i.e., G-PCC encoders inherently operate spatial regions (e.g., Voxel blocks or octree nodes)) determining a motion compensated point within a current prediction unit by performing local motion compensation on the current prediction unit; (Cao,[0004] “… a G-PCC encoder may apply “global” motion compensation to the reference frame (e.g., a predicted frame) to account for a rotation of the entire reference frame and/or a translation of the entire reference frame., In this example the G-PCC encoder may apply “local” motion estimation to account for a rotation and/or translation at a finer scale than the global motion compensation.” See also ¶[0083]) and Cao does not explicitly disclose determining geometric information of a current point within the current prediction unit based on the motion compensated point, wherein the geometric information of the current point is determined based on at least one of the motion compensated point or a point included in a plane of at least one triangle, wherein the point included in the plane of the at least one triangle is determined based on the motion compensated point, and wherein the at least one triangle is generated based on the motion compensated point. However, in the same field of endeavor Flynn discloses more explicitly the following: determining geometric information of a current point within the current prediction unit based on the motion compensated point, wherein the geometric information of the current point is determined based on at least one of the motion compensated point or a point included in a plane of at least one triangle, wherein the point included in the plane of the at least one triangle is determined based on the motion compensated point, and wherein the at least one triangle is generated based on the motion compensated point. (Flynn, Col, 4 lines 12-17 “A point cloud is a set of points in a three-dimensional coordinate system. The points are often intended to represent the external surface of one or more objects. Each point has a location (position) in the three-dimensional coordinate system. The position may be represented by three coordinates (X, Y, Z), …” Col, 5 lines 25-31 “ The point cloud encoder …includes a tree building module … for receiving point cloud data and producing a tree (in this example, an octree) representing the geometry of the volumetric space containing point cloud and indicating the location or position of points from the point cloud in that geometry.”) Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the application to modify the teachings of Cao with Flynn to create the system of Cao as outlined above in order to “determine geometric information of a current point within the current prediction unit based on the motion compensated point, wherein the geometric information of the current point is determined based on at least one of the motion compensated point” as suggested by Flynn. A person of ordinary skill would have been motivated to do so to increase an accuracy of a motion-compensated predicted frame, thereby reducing a residual data and improving coding efficiency,” (Flynn. [0005]) Note: The motivation that was utilized in the rejection of claim 1, applies equally as well to claims 2-5, and 9-11. Regarding Claim 2 Cao-Flynn Cao-Flynn discloses 2. (Original) The method of claim 1, wherein determining the geometric information of the current point comprises: deriving a predicted statistical value based on a motion compensated point included in a predefined specific area around the current point. (Col. 7, lines 56-60, “As an example, FIG. 6 shows the cube 200 in which the four “front” sub-cubes are occupied. This would correspond to pattern 85, on the basis that the sub-cubes occupied are cubes 1+4+16+64. The integer pattern number specifies the pattern of occupancy in the sub-cubes.” See Fig. 6 (e.g., cubes 1, 4, 16, 64) are shown as occupied. This directly corresponds to determining the geometric information (occupancy) of points within the predication unit) and determining the geometric information of the current point based on the predicted statistical value. (Flynn, Col. 8, 31-38) “In operation 202, the encoder determines the pattern of occupancy for the current node. The current node is an occupied node that has been split into eight child nodes, each corresponding to a respective sub-cube. The pattern of occupancy for the current node specifies the occupancy of the eight child nodes in scan order. As described above, this pattern of occupancy may be indicated using an integer between 1 and 255, e.g. an eight-bit binary string”) Regarding Claim 3 Cao-Flynn Cao-Flynn discloses 3. (Original) The method of claim 2, wherein the geometric information of the current point includes a symbol indicating whether the current point is occupied, . (Flynn, Col, 7, lines 31-35 ”The entropy encoder then encodes that pattern using a non-binary arithmetic encoder based on probabilities specified by the context model. In this example, the probabilities may be a pattern distribution based on an initial distribution model and adaptively updated”) and wherein the symbol indicating whether the current point is occupied is entropy encoded using the predicted statistical value as a probability. (Flynn, Col, 7, lines 33-42 “In this example, the probabilities may be a pattern distribution based on an initial distribution model and adaptively updated. In one implementation, the pattern distribution is effectively a counter of the number of times each pattern (integer from 1 to 255) has been encountered during coding. The pattern distribution may be updated after each sub-volume is coded. The pattern distribution may be normalized, as needed, since the relative frequency of the patterns is germane to the probability assessment and not the absolute count”) Regarding Claim 4 Cao-Flynn Cao-Flynn discloses 4. (Original) The method of claim 2, wherein the specific area around the current point is defined as an area including voxels adjacent to front, back, left, right, upper, and lower sides of the current point. (Flynn, Col. 9, lines 24-28 “FIG. 9 illustrates a set of neighbors surrounding a current node, where neighbor is defined as nodes sharing a face. In this example, the nodes/sub-volumes are cubes and the cube at the center of the image has six neighbors, one for each face.” These face-sharing neighbors directly correspond to voxels on six sides of the cube, such as cubes 1, 2, 4, 8, 16, 32 in Fig. 9) Regarding Claim 5 Cao-Flynn Cao-Flynn discloses 5. (Original) The method of claim 2, wherein the specific area around the current point is defined as a hexahedral area centered on the current point and including adjacent voxels adjacent to the current point. (Flynn, Col. 9, lines 38-41“…the neighbor definition may be broadened to include neighboring nodes based on a shared edge or based on a shared vertex to include additional adjacent sub-volumes in the assessment.” i.e., including edge-and vertex-sharing neighbors in addition to face neighbors defines the full cube of surrounding voxels, which corresponds to the hexahedral region”) Regarding Claim 6-7 (Canceled) Regarding Claim 9 Cao-Flynn Cao-Flynn discloses 9. (Original) The method of claim 1, wherein the current prediction unit is divided into areas having a size of 1x1x1 based on a predefined tree structure, (Col. 4, lines 54-58 One of the more common mechanisms for coding point cloud data is through using tree-based structures. In a tree-based structure, the bounding three-dimensional volume for the point cloud is recursively divided into sub-volumes. (Col. 6, lines 63-67 and Col. 7, lines 1-4; Fig. 3 “…. the size of the sub-volume 100 is 16×16. It will be noted that the sub-volume has been divided into four 8×8 sub-squares, and two of those have been further subdivided into 4×4 sub-squares, three of which are further divided to 2×2 sub-squares, and one of the 2×2 sub-square is then divided into 1×1 squares. The 1×1 squares are the maximum depth of the tree and represent the finest resolution for positional point data”) and wherein the current point corresponds to a central position of an area having the size of 1x1x1 (Col. 6, lines 61-67 and Col. 7, lines 1-4 “FIG. 3. In this example, a slice of the sub-volume 100 is shown in two-dimensions for ease of illustration, and the size of the sub-volume 100 is 16×16. It will be noted that the sub-volume has been divided into four 8×8 sub-squares, and two of those have been further subdivided into 4×4 sub-squares, three of which are further divided to 2×2 sub-squares, and one of the 2×2 sub-square is then divided into 1×1 squares. The 1×1 squares are the maximum depth of the tree and represent the finest resolution for positional point data”) Regarding Claim 10 Cao-Flynn Cao-Flynn discloses 10. (Original) The method of claim 9, wherein the predefined tree structure includes at least one of a binary tree, a quad tree, or an oct tree. (Flynn, Col, 5, lines 1-4 “A commonly-used tree structure is an octree. In this structure, the volumes/sub-volumes are all cubes and each split of a sub-volume results in eight further sub-volumes/sub-cubes.”) Regarding Claim 11 Cao-Flynn Cao discloses A device for compressing a point cloud, (Cao, [0006] “A device for encoding point cloud data…”) comprising: a processor configured to control the device; (Cao, [0006] “...the device…one or more processors coupled … and implemented in circuitry.”) and a memory coupled with the processor and configured to store data. (Cao, [0006] “The device comprising a memory to store the point cloud data and one or more processors coupled to tire memory and implemented in circuitry.”) wherein the processor is configured to: The remaining limitations of independent claim 11 recite features that are substantially similar to those set forth in independent claim 1. Accordingly, the reasoning and analysis provided with respect to claim 1 apply equally to claim 11. Claim Rejections - 35 USC § 103 9. Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Cao-Flynn in further view of Zhang et al (US-20220124374-A1) hereinafter “Zhang”. Regarding Claim 8 Cao-Flynn-Zhang Cao-Flynn-Zhang discloses 1. (Currently Amended) The method of claim [[6]] 1, wherein dividing into the at least one triangle comprises: obtaining a plurality of vertices based on a plurality of motion compensated points adjacent to edges of the current prediction unit; (Zhang, [0029] “Based on a surface formed by distribution of the point cloud in each block, at most twelve vertexes generated by both the surface and twelve edges of the block are obtained….”) and dividing the current prediction unit into the at least one triangle by connecting the plurality of vertices. (Zhang, [0029] “Perform arithmetic coding on nodes in the leaf nodes to generate a binary geometry bitstream,…,During encoding of the geometry information based on triangle soup (trisoup), octree partition is also performed first.”) Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the application to modify the teachings of Cao-Flynn with Zhang to create the system of Cao-Flynn as outlined above in order to perform “obtaining a plurality of vertices based on a plurality of motion compensated points adjacent to edges of the current prediction unit; and dividing the current prediction unit into the at least one triangle by connecting the plurality of vertices.” as suggested by Zhang. One of ordinary skill in the art would have been motivated to incorporate Zhang’s teaching into Cao-Flynn system because doing so would greatly improve the coding efficiency. (Zhang, [0059]). Pertinent Prior Art 10. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure OH et al. US-20220130075-A1 Conclusion 11. THIS ACTION IS MADE FINAL. 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. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ASTEWAYE GETTU ZEWEDE whose telephone number is (703)756-1441. The examiner can normally be reached Mo-Fr 8:30 am to 5:30 pm. 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, William Vaughn can be reached at (571)272-3922. 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. /ASTEWAYE GETTU ZEWEDE/Examiner, Art Unit 2481 /WILLIAM C VAUGHN JR/Supervisory Patent Examiner, Art Unit 2481
Read full office action

Prosecution Timeline

Oct 28, 2024
Application Filed
Oct 02, 2025
Non-Final Rejection — §103
Jan 16, 2026
Response Filed
Mar 18, 2026
Final Rejection — §103 (current)

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Prosecution Projections

3-4
Expected OA Rounds
80%
Grant Probability
99%
With Interview (+37.5%)
2y 7m
Median Time to Grant
Moderate
PTA Risk
Based on 45 resolved cases by this examiner. Grant probability derived from career allow rate.

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