Prosecution Insights
Last updated: August 17, 2026
Application No. 19/015,188

NEW CONDITIONAL CODING FOR LEARNING-BASED DYNAMIC POINT CLOUD CODING FRAMEWORK

Final Rejection §102§112
Filed
Jan 09, 2025
Examiner
MAHMUD, FARHAN
Art Unit
2483
Tech Center
2400 — Computer Networks
Assignee
InterDigital Inc.
OA Round
2 (Final)
56%
Grant Probability
Moderate
3-4
OA Rounds
2y 0m
Est. Remaining
66%
With Interview

Examiner Intelligence

Grants 56% of resolved cases
56%
Career Allowance Rate
221 granted / 395 resolved
-2.1% vs TC avg
Moderate +10% lift
Without
With
+10.2%
Interview Lift
resolved cases with interview
Typical timeline
3y 7m
Avg Prosecution
29 currently pending
Career history
439
Total Applications
across all art units

Statute-Specific Performance

§101
5.4%
-34.6% vs TC avg
§103
49.1%
+9.1% vs TC avg
§102
34.5%
-5.5% vs TC avg
§112
8.7%
-31.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 395 resolved cases

Office Action

§102 §112
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 Applicant previously filed claims 1-20. Claims 4 and 14 have been cancelled. Claims 1, 10 and 11 have been amended. Accordingly, claims 1-3, 5-13, and 15-20 are pending in the current application. Response to Arguments Applicant's arguments filed 05/13/2026 have been fully considered but they are not persuasive. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “temporal domain”; “generating an inter feature” in claim 1) 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). Applicant argues that Kwong et al. fails to teach “wherein obtaining the second feature comprises alternating between the first feature and the predicted feature to use as the second feature”. However, examiner respectfully disagrees. In Paragraph 57, Kwong et al. teaches “Using the analogous point cloud predicted from the geometric prior, geometry compression performance of the source point cloud can be promoted by redundancy removal. Specifically, some embodiments extract high-level feature representations of the source and the aligned point clouds separately using stacked downsampling blocks. Since the aligned point cloud refers to a coarse approximation of the target positions, warping operations are carried out within the feature space, following the techniques used in deep video compression for feature-level motion estimation and motion compensation [33]. More precisely, the features of the aligned point cloud are warped onto the coordinates of the source point cloud using sparse convolution. This allows compact residual features to be obtained through feature subtraction, followed by the compression of residual features. It is worth noting that the proposed pipeline is versatile and can be applied in a plug-and-play fashion by swapping out the feature extraction and warping modules with a variety of approaches. In one implementation, the feature extraction and warping techniques are inherited from the aforementioned deep point cloud compression approaches [10], [42], [49] based on sparse convolution [62] to retain essential and critical point characteristics.” The described high level feature representations of the source and the aligned point clouds, and the associated description swapping out a variety of approaches to arrive at a second feature are interpreted to meet the claim limitations as filed Applicant is again reminded that 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). In light of the above remarks, the claims are rejected as before. 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 5 and 15 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 5 recites the limitation "the method of claim 4". Claim 4 has been cancelled, so there is insufficient antecedent basis for this limitation in the claim. Claim 15 recites the limitation "the method of claim 14". Claim 14 has been cancelled, so there is insufficient antecedent basis for this limitation in the claim. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claim(s) 1-3, 5-13, and 15-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kwong et al. (US 20250045970 A1). Regarding Claim 10, Kwong et al. teaches an apparatus comprising: a processor; and a memory storing instructions operative, when executed by the processor (Paragraphs 17-18), to cause the apparatus to: decode a motion feature from a motion bitstream (Paragraphs 57-63; Paragraphs 65-66); determine a predicted feature based on the decoded motion feature and a reference point cloud frame (Paragraphs 65-66; Paragraph 70); decode a first feature representing an occupancy of a child level (Paragraphs 44-47; Paragraphs 66-67); obtain a second feature based on the decoded first feature and the predicted feature (Paragraphs 57-64; Paragraphs 65-66; Paragraphs 73- 78), wherein obtaining the second feature comprises alternating between the first feature and the predicted feature to use as the second feature (Paragraphs 57-64; Paragraphs 65-66; Paragraphs 73- 78); and determine a tree voxel occupancy status of the child level using the second feature (Paragraph 44; Paragraphs 46-47; Paragraphs 56-64; Paragraphs 65-69; Paragraphs 73-78). Method claim 1 is drawn to the method of using apparatus claim 10, and is rejected for the same reasons as used above. Regarding Claim 2, Kwong et al. teaches the method of claim 1, further comprising obtaining the motion bitstream (Paragraph 5; Paragraphs 57-63; Paragraphs 65-66). Regarding Claim 3, Kwong et al. teaches the method of claim 1, wherein obtaining the second feature comprises adding the first feature and the predicted feature (Paragraph 14; Paragraphs 65-66; Paragraph 92). Regarding Claim 5, Kwong et al. teaches the method of claim 4, wherein the first feature corresponds to an intra feature and the predicted feature corresponds to an inter feature (Paragraphs 44-45; Paragraphs 57-64; Paragraphs 65-66; Paragraphs 73-78). Regarding Claim 6, Kwong et al. teaches the method of claim 1, further comprising passing the obtained second feature through a convolutional neural network (CNN) (Paragraph 47; Paragraphs 57-64; Paragraphs 65-66; Paragraphs 73-78; Paragraphs 89-90). Regarding Claim 7, Kwong et al. teaches the method of claim 6, wherein the output of the CNN comprises a reconstructed feature (Paragraph 47; Paragraphs 57-64; Paragraphs 65-66; Paragraphs 73-78; Paragraphs 89-90). Regarding Claim 8, Kwong et al. teaches the method of claim 1, further comprising passing the obtained second feature through at least one of a Multi- Layer Perceptron (MLP) block, an Inception ResNet (IRN) block, or a transformer block (Paragraph 47; Paragraphs 57-64; Paragraphs 65-66; Paragraphs 73-78; Paragraphs 89-90). Regarding Claim 9, Kwong et al. teaches the method of claim 1, further comprising generating a reconstructed feature using the first feature and the predicted feature (Paragraph 5; Paragraphs 14-15; Paragraphs 56-64; Paragraphs 65-66; Paragraphs 78-79). Method claims 11, 13, 15, 16, and 18 are drawn to the encoding method corresponding to the decoding method of claims 1, 3, 5, 6, and 8 above, these claims recite similar limitations merely performed in the inverse, and are rejected for the same reasons as used above. Kwong et al. further teaches determining a motion feature from a current point cloud and at least one of one or more reference point cloud frames; determining a predicted feature based on the motion feature; encoding the motion feature into a bitstream (Paragraph 5; Paragraphs 47-48; Paragraphs 52-53; Paragraph 56; Paragraph 60). Regarding Claim 12, Kwong et al. teaches the method of claim 11, further comprising obtaining the current point cloud geometry based on the one or more reference point cloud frames (Paragraphs 47-48; Paragraphs 52-53; Paragraph 58; Paragraph 70). Regarding Claim 17, Kwong et al. teaches the method of claim 16, further comprising: conditionally encoding an output of the CNN, wherein the conditionally encoded output comprises a lossy feature; and inserting the conditionally encoded output into a bitstream (Paragraph 44; Paragraph 47; Paragraphs 57-64; Paragraphs 65-66; Paragraphs 67-69; Paragraphs 73-78; Paragraphs 89-90). Regarding Claim 19, Kwong et al. teaches the method of claim 11, further comprising: using the first feature and the predicted feature to generate a feature to be encoded; and encoding into the bitstream the feature to be encoded (Paragraph 5; Paragraphs 47-48; Paragraphs 52-53; Paragraph 56; Paragraph 60; Paragraph 77). Regarding Claim 20, Kwong et al. teaches the method of claim 11, wherein determining the first feature comprises: obtaining a feature map; obtaining coordinates of a lossy reconstruction of a parent level; and performing a feature interpolation to generate the first feature, wherein the feature map and the coordinates of the lossy reconstruction of the parent level are used as inputs into the feature interpolation (Paragraph 44; Paragraph 47; Paragraphs 57-64; Paragraphs 65-66; Paragraphs 67-71; Paragraphs 73-78; Paragraphs 89-90). Conclusion 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 FARHAN MAHMUD whose telephone number is (571)272-7712. The examiner can normally be reached 10-7. 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, Joseph Ustaris can be reached at 5712727383. 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. /FARHAN MAHMUD/Primary Examiner, Art Unit 2483
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Prosecution Timeline

Jan 09, 2025
Application Filed
Jan 15, 2026
Non-Final Rejection mailed — §102, §112
May 13, 2026
Response Filed
Jul 23, 2026
Final Rejection mailed — §102, §112 (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
56%
Grant Probability
66%
With Interview (+10.2%)
3y 7m (~2y 0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 395 resolved cases by this examiner. Grant probability derived from career allowance rate.

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