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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 February 26, 2026 has been entered.
Response to Arguments
Applicant’s arguments, see pp.5-6, filed February 26, 2026, with respect to the rejection(s) of claim(s) 1 under 35 U.S.C § 103, specifically the argument that the prior art does not teach or suggest the limitation “wherein the prediction list is updated based on an azimuth for the point cloud data, have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of newly considered prior art.
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) 1-2, 10-11, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over XU et al. (US 2024/0249441) in view of Xu et al. (US 2024/0357174) further in view of Taquet et al. (US 2024/0185466).
Regarding claim 1 Xu ‘441 discloses a method comprising:
encoding geometry data of point cloud data; and encoding attribute data of the point cloud data (inter prediction for geometry coding and attribute coding – [0005, 0077]; coding (encoding and/or decoding) point cloud data – [0028, 0031]),
wherein the encoding the geometry data includes:
generating a prediction list including point indexes of a point; and inter-predicting based on a prediction list including point indexes (Figure 4 shows that for each point, the previous decoded point will be chosen as point A. Then the point in the reference frame with the same scaled azimuth and laser ID as point A will be selected as point B. At last, the point in the reference frame which is the first point that has scaled azimuth greater than that of point B will be chosen as point C. The codec will use the geometry information of the point C to perform the prediction coding for the geometry information of the current point – description of Fig. 4; the geometry information of the reference PC samples may be used to perform the geometry inter prediction for the current PC sample – [0125]; the predicted geometry value may be selected from some candidate predictors; a candidate predictor may be derived by one or multiple geometry values of the reference samples or may be derived as a function of one or multiple geometry values of the reference PC samples or may be derived by one or multiple predicted geometry values of the current PC sample or previous decoded samples or may be derived as a function of one or multiple predicted geometry values of the current PC sample or previous decoded samples – [0127]).
However, fails to explicitly disclose generating a prediction list including point indexes for an angular coordinate of a point; and inter-predicting the angular coordinate of the point based on the list, wherein the prediction list is updated based on an azimuth for the point cloud data.
In his disclosure Xu ‘174 teaches generating a prediction list including point indexes for an angular coordinate of a point; and inter-predicting the angular coordinate of the point based on the list (for inter prediction and the creation of list1 reordering pf the point may be performed based on spherical coordinates or cylindrical coordinates of the points – [0087-0097]; it is also disclosed that inter-prediction may be performed in different coordinate systems such as spherical coordinate system, cylindrical coordinate system, and so on – [0160]).
Xu ‘174 further teaches updating the prediction data (in G-PCC, two neighbor lists, list1 and list2, are built to search 3 approximately nearest neighbors of the current point. List1 contains 3 approximately nearest neighbors which are obtained by a LOD based approximately nearest neighbors search algorithm. List2 contains 3 points that are dropped out when updating list1 – [0072-0074]).
It would be obvious to a person with ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the teachings of Xu ‘174 into the teachings of Xu ‘441 because such incorporation improves the efficiency of point cloud coding (paragraph 271).
However, fails to explicitly disclose wherein the prediction list is updated based on an azimuth for the point cloud data.
In his disclosure Taquet teaches updating prediction data based on azimuthal angles (paragraph 166).
It would have been obvious to a person with ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the teachings of Taquet into the teachings of Xu ‘441 as modified because such incorporation improves to improves the compression performance of the point cloud, for example, the total bitrate to encode/decode the point cloud data can be improved (paragraph 107).
Regarding claim 2 Xu ‘441 discloses the method of claim 1, wherein the encoding the geometry data further comprises:
clustering the point cloud data (a plurality of consecutive frames of the point cloud sequence in time stamp order may be clustered as one GOF – [0357]); and
selecting a first point related to a cluster generated in the clustering (the points in the point cloud are sorted to form a predictive tree. As shown in FIG. 4, for each point, the previous decoded point will be chosen as point A – [0081]).
In regards to claim 10, any encoder technology that is present in an encoder also necessarily needs to be present, in substantially identical form in a corresponding decoder. The description of decoder technologies can be abbreviated as they are the inverse of the comprehensively described encoder technologies. Therefore, claim 10 is being rejected on the same basis as claim 1.
In regards to claim 11, any encoder technology that is present in an encoder also necessarily needs to be present, in substantially identical form in a corresponding decoder. The description of decoder technologies can be abbreviated as they are the inverse of the comprehensively described encoder technologies. Therefore, claim 11 is being rejected on the same basis as claim 2.
Claim 18 is being rejected on the same basis as claim 1. It is noted Xu ‘441 discloses encoded point data being transmitted to the destination device (paragraph 31).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over XU et al. (US 2024/0249441) in view of Xu et al. (US 2024/0357174) further in view of Taquet et al. (US 2024/0185466) further in view of Korean Application KR 20200026097A.
Regarding claim 3 Xu ‘441 discloses the method of claim 2. However, Xu ‘441 is silent on wherein the first point is a point closest to a mean of points included in the cluster.
The disclosure in 097A teaches about the clustering of point cloud data, selecting a first point related to a cluster generated in the clustering (clustering 3D points – [0010, 0018]; determining a core point that is related to DBSCAN clustering), and wherein the first point is a point closest to a mean of points included in the cluster (the point cloud service 100 first sets a minimum distance (Eps) and a minimum number of data (MinPts) for DBSCAN clustering, and a neighboring area corresponding to a minimum distance (Eps) from a specific three-dimensional point. If there are 3D points greater than or equal to the minimum number of data points (MinPts), the 3D point becomes a core point – [0065]; DBSCCAN clustering ,ay refer to a process of grouping the corresponding area into one point cluster when the density of the corresponding area is high because 3D points are densely clustered in a predetermined area – [0063]).
It would have been obvious to a person with ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the teachings of 097A into the teachings of Xu ‘441 because such incorporation improves versatility by not being limited by the form of the cluster and it is not necessary to specify the number of clusters (paragraph 63).
Claim(s) 4, 6-8, 12-13, and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over XU et al. (US 2024/0249441) in view of Xu et al. (US 2024/0357174) further in view of Taquet et al. (US 2024/0185466) further in view of Korean Application KR 20200026097A further in view of Hur et al. (WO 2020/197086A1).
Regarding claim 4 Xu ‘441 discloses the method of claim 3. However, fails to explicitly disclose wherein the prediction list is generated based on the first point, wherein points between a plurality of frames are predicted based on the prediction list.
In his disclosure Hur teaches the prediction list is generated based on the first point, wherein points between a plurality of frames are predicted based on the prediction list (obtaining a set of neighboring points to predict a point – p.24, Figures 9 and 10 description; p.25, 3rd paragraph, refer to description translation).
It would have been obvious to a person with ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the teachings of Hur into the teachings of Xu ‘441 because such incorporation provides a better compression efficiency (p.25, 3rd paragraph of description translation).
Regarding claim 6 Xu ‘441 discloses the method of claim 4. However, fails to explicitly disclose wherein a bitstream including the geometry data and the attribute data contains information indicating whether the clustering is performed.
In his disclosure Hur teaches wherein a bitstream including the geometry data and the attribute data contains information indicating whether the clustering is performed (generate and/or process signaling information related to geometry encoding and/or attribute encoding; in addition, signaling information according to embodiments may be interleaved – p.17, 8th paragraph; p.18, 3rd paragraph).
It would have been obvious to a person with ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the teachings of Hur into the teachings of Xu ‘441 because the person with ordinary skill in the art would know that signaling encoding/decoding information is a well-known technique in the art and yields expected results.
Regarding claim 7 Xu ‘441 discloses the method of claim 6. However, fails to explicitly disclose wherein the bitstream contains information indicating a method to perform the clustering.
In his disclosure Hur teaches the bitstream contains information indicating a method to perform the clustering (generate and/or process signaling information related to geometry encoding and/or attribute encoding; in addition, signaling information according to embodiments may be interleaved – p.17, 8th paragraph; p.18, 3rd paragraph).
It would have been obvious to a person with ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the teachings of Hur into the teachings of Xu ‘441 because the person with ordinary skill in the art would know that signaling encoding/decoding information is a well-known technique in the art and yields expected results.
Regarding claim 8 Xu ‘441 discloses the method of claim 7. However, fails to explicitly disclose wherein the encoding further comprises: segmenting the frames.
The disclosure of 097A teaches segmenting the frames (applying region segmentation to an image input – [0069-0070]).
It would have been obvious to a person with ordinary skill in the art, before the effective filing date of the claimed invention, to incorporate the teachings of 097A into the teachings of Xu ‘441 because such incorporation improves versatility by not being limited by the form of the cluster and it is not necessary to specify the number of clusters (paragraph 63).
In regards to claim 12, any encoder technology that is present in an encoder also necessarily needs to be present, in substantially identical form in a corresponding decoder. The description of decoder technologies can be abbreviated as they are the inverse of the comprehensively described encoder technologies. Therefore, claim 12 is being rejected on the same basis as claims 3 and 4.
In regards to claim 13, any encoder technology that is present in an encoder also necessarily needs to be present, in substantially identical form in a corresponding decoder. The description of decoder technologies can be abbreviated as they are the inverse of the comprehensively described encoder technologies. Therefore, claim 13 is being rejected on the same basis as claim 4.
In regards to claim 14, any encoder technology that is present in an encoder also necessarily needs to be present, in substantially identical form in a corresponding decoder. The description of decoder technologies can be abbreviated as they are the inverse of the comprehensively described encoder technologies. Therefore, claim 14 is being rejected on the same basis as claims 6 and 7.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARIA E VAZQUEZ COLON whose telephone number is (571)270-1103. The examiner can normally be reached M-F 7:30 AM-3:30 PM.
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/MARIA E VAZQUEZ COLON/ Examiner, Art Unit 2482
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