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 .
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.
Claim(s) 1-3, 5, and 15-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhu et al. (US 20240087176 A1) in view of Yang et al. (US 20240062429 A1).
Regarding claim 1, Zhu discloses a point cloud decoding method ([0044], [0063], and [0067]), comprising:
determining a decoding mode ([0084] to [0086] an attribute decoding mode of prediction attribute information of each point in the target point cloud group according to reconstruction attribute information of the point in the associated point cloud group of the target point cloud group) a current point,
in a case where the decoding mode of the current point is a skip decode mode (skipDecodeMode) ([0065] skipping a current to be decoded point, so skipping a current to be decoded point would obviously be considered as skipDeodeMode; [0067] the point C may be skipped; [0073] skipping performing grouping processing on a current to-be-decoded point in a case that the current to-be-decoded point is a repeated point), determining at least one prediction point of the current point among points ([0119] determining a prediction attribute value of the target point according to the geometric relationship between the Q neighboring points and the target point and reconstruction attribute information of the Q neighboring points; the Q neighboring points being Q points that are in the point cloud group obtained by performing grouping processing on the to-be-decoded point cloud data and that are geometrically close to the target point, [0122], [0126], and [0127]),
the skipDecodeMode is a mode for skipping decoding of geometric information of the current point ([0027] Geometric information of any point may be referred to as three-dimensional coordinates (x, y, z) of the point. The attribute information of any point may include at least one of the following: color information, material information, and laser reflection intensity information (which may also be referred to as reflectivity). Each point in the point cloud data may have the same quantity of attribute information; [0065] skipping a current to-be-decoded point in a case that the current to-be-decoded point is a repeated point; [0066] That the current to-be-decoded point is a repeated point may mean that geometric information of the current to-be-decoded point is the same as geometric information of any preceding point of the current to-be-decoded point. That geometric information of the current to-be-decoded point is the same as geometric information of the preceding point may mean that: Three-dimensional coordinates of the current to-be-decoded point are the same as three-dimensional coordinates of the preceding point, that is, the current to-be-decoded point is overlapped with the preceding point in three-dimensional space; [0207] and [0208] skipping a current to-be-decoded point in a case that the current to-be-decoded point is a repeated point, and that the current to-be-decoded point being a repeated point meaning that geometric information of the current to-be-decoded point is the same as geometric information of any preceding point of the current to-be-decoded point; [0213] and [0214] skipping performing grouping processing on a current to-be-decoded point in a case that the current to-be-decoded point is a repeated point, and a quantity of counted repeated points is greater than a first quantity threshold); and
determining the geometric information of the current point based on geometric information of the at least one prediction point ([0027] Geometric information of any point may be referred to as three-dimensional coordinates (x, y, z) of the point. Each point in the point cloud data may have the same quantity of attribute information; [0063] and [0066] three dimensional coordinates of the current to be decoded point, [0119] determining a prediction attribute value of the target point according to the geometric relationship between the Q neighboring points and the target point and reconstruction attribute information of the Q neighboring points).
It is noted that Zhu is silent about the current point in a current node, wherein the current node is a node to be decoded in a current picture to be decoded, the prediction point comprised in N prediction nodes of the current node, N is a positive integer, and wherein the prediction nodes are nodes corresponding to the current node in prediction reference pictures of the current picture to be decoded.
Zhang teaches the current point in in a current node ([0034] to [0036] each point that includes the current point in the current node), wherein the current node is a node to be decoded in a current picture to be decoded ([0043] to [0047] obtaining a geometric information bitstream and decoding the geometric information bitstream to obtain decoded data, where the decoded data includes a prediction mode for a current node and reconstructing a point cloud according to the predicted residual in the Cartesian coordinate system and the predicted Cartesian coordinates to obtain reconstructed point cloud data); the prediction point comprised in N prediction nodes of the current node, N is a positive integer ([0121] and [0122] prediction point; [0123] and [0125] the quantity of child nodes and a prediction mode for the current node and other information, are used as to-be-coded information, the quantity of the nodes is considered as a positive integer) and wherein the prediction nodes are nodes corresponding to the current node in prediction reference pictures of the current picture to be decoded ([0123] and [0125] for the to-be-coded information of each node, first, the quantity of child nodes of the current node needs to be coded, and second, the prediction mode for the) current node, the predicted residual (r.sub.r,r.sub.j,r.sub.i) the predicted residual (r.sub.x,r.sub.y,r.sub.z) respectively corresponding to the current node, and the predicted residual {circumflex over (n)} of the points that need to be skipped are coded).
Taking the teachings of Zhu and Yang together as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the prediction nodes of Yang into the prediction points of Zhu to reduce geometric structural distortion of a model as much as possible, thereby improving geometry coding efficiency.
Regarding claim 2, Zhu teaches the method according to claim 1, Zhu further teaches wherein determining the decoding mode of the current point in the current node comprises:
determining whether the current node ([0032] and [0033] a current node) meets a start condition of the skipDecodeMode ([0203] performing transform determining on the target point cloud group; the target point cloud group meets a transform condition; and the target point cloud group meets the transform condition including any one of the following: a quantity of points included in the target point cloud group meets a quantity condition, or distribution of the reconstruction residual information of each point in the target point cloud group meets a distribution condition); and
determining the decoding mode of the current point based on whether the current node meets the start condition of the skipDecodeMode ([0204] an attribute decoding mode of the first point cloud group is different from the attribute decoding mode of the target point cloud group; or an attribute decoding mode of the first point cloud group is the same as the attribute decoding mode of the target point cloud group; [0208] skipping a current to-be-decoded point in a case that the current to-be-decoded point is a repeated point).
Regarding claim 3, Zhu teaches the method according to claim 2, wherein determining the decoding mode of the current point according to whether the current node meets the start condition of the skipDecodeMode ([0204] an attribute decoding mode of the first point cloud group is different from the attribute decoding mode of the target point cloud group; or an attribute decoding mode of the first point cloud group is the same as the attribute decoding mode of the target point cloud group; [0208] skipping a current to-be-decoded point in a case that the current to-be-decoded point is a repeated point) comprises:
in a case where the current node ([0032] and [0033] for a current node) meets the start condition of the skipDecodeMode ([0192] the target point cloud group meets the transform condition may include any one of the following: A quantity of points included in the target point cloud group meets a quantity condition),
determining that a decoding mode of geometric information for at least one component of the current point is the skipDecodeMode ([0027] Geometric information of any point may be referred to as three-dimensional coordinates (x, y, z) of the point, and may include coordinates of the point on each coordinate axis of the three-dimensional coordinate system, that is, coordinate x of an X axis, coordinate y of a Y axis, and coordinate z of a Z axis. The attribute information of any point may include at least one of the following: color information, material information, and laser reflection intensity information (which may also be referred to as reflectivity). Each point in the point cloud data may have the same quantity of attribute information, [0063] and [0066] three dimensional coordinates of the current to be decoded point; [0203] performing transform determining on the target point cloud group; the target point cloud group meets a transform condition and the target point cloud group meets the transform condition including any one of the following: a quantity of points included in the target point cloud group meets a quantity condition, or distribution of the reconstruction residual information of each point in the target point cloud group meets a distribution condition; [0208] skipping a current to-be-decoded point in a case that the current to-be-decoded point is a repeated point; [0204] and [0215] decoding mode); or
determining the decoding mode of the current point according to whether the current node meets the start condition of the skipDecodeMode comprises: in a case where the current node meets the start condition of the skipDecodeMode, decoding a bitstream to obtain a first flag, wherein the first flag is used to indicate whether the current point uses the skipDecodeMode, and the first flag is determined based on an error between the geometric information of the current point and the geometric information of the at least one prediction point; and determining the decoding mode of the current point based on the first flag.
Regarding claim 5, Zhu teaches the method according to claim 2, Zhu further teaches wherein the start condition of the skipDecodeMode comprises any one of: a number of points comprised in the prediction nodes being greater than or equal to a first numerical value ([0073] skipping performing grouping processing on a current to-be-decoded point in a case that the current to-be-decoded point is a repeated point, and a quantity of counted repeated points is greater than a first quantity threshold; [0214] skipping performing grouping processing on a current to-be-decoded point in a case that the current to-be-decoded point is a repeated point, and a quantity of counted repeated points is greater than a first quantity threshold; and performing grouping processing on the current to-be-decoded point in a case that the current to-be-decoded point is a repeated point, but the quantity of counted repeated points is less than or equal to the first quantity threshold); the number of points comprised in the prediction nodes being equal to a number of points comprised in the current node; or the number of points comprised in the prediction nodes being equal to the number of points comprised in the current node, and a direct decoding mode of the prediction nodes being the same as a direct decoding mode of the current node.
Regarding claim 15, Zhu teaches the method according to claim 1, Zhu further teaches wherein determining the geometric information of the current point based on the geometric information of the at least one prediction point ([0027] geometric information, [0055] obtaining geometric information of each point) comprises:
obtaining first geometric information based on the geometric information of the at least one prediction point ([0055] the decoding device 202 may obtain reconstruction geometric information of points in each point cloud group. The decoding device 202 may establish a one-to-one correspondence between the reconstruction attribute information and the reconstruction geometric information of points in each point cloud group, and reconstruct point cloud data according to the reconstruction attribute information and the reconstruction geometric information of points in each point cloud group; [0063] The preceding point of the current to-be-decoded point may be a point whose decoding sequence is before that of the current to-be-decoded point. That the current to-be-decoded point is a repeated point may mean that geometric information of the current to-be-decoded point is the same as geometric information of any preceding point of the current to-be-decoded point); and
determining geometric information for at least one component of the current point based on the first geometric information ([0027] Geometric information of any point may be referred to as three-dimensional coordinates (x, y, z) of the point, and may include coordinates of the point on each coordinate axis of the three-dimensional coordinate system, that is, coordinate x of an X axis, coordinate y of a Y axis, and coordinate z of a Z axis. The attribute information of any point may include at least one of the following: color information, material information, and laser reflection intensity information (which may also be referred to as reflectivity). Each point in the point cloud data may have the same quantity of attribute information, [0063] and [0066] three dimensional coordinates of the current to be decoded point; [0069] That the current to-be-decoded point is a repeated point may mean that geometric information of the current to-be-decoded point is the same as geometric information of any preceding point of the current to-be-decoded point. That geometric information of the current to-be-decoded point is the same as geometric information of the preceding point may mean that: Three-dimensional coordinates of the current to-be-decoded point are the same as three-dimensional coordinates of the preceding point, that is, the current to-be-decoded point is overlapped with the preceding point in three-dimensional space. That any to-be-decoded point is a non-repeated point may mean that geometric information of the to-be-decoded point is different from geometric information of all preceding points of the to-be-decoded point. The grouping quantity threshold may refer to a maximum quantity of points that the current point cloud group allows to accommodate).
Regarding claim 16, Zhu teaches the method according to claim 15, Zhu further teaches wherein obtaining the first geometric information based on the geometric information of the at least one prediction point comprises: determining an average of the geometric information of the at least one prediction point as the first geometric information ([0219] an average value of prediction attribute information of the target points as the prediction attribute information of each point in the target point cloud group).
Regarding claim 17, Zhu teaches the method according to claim 15, Zhu further teaches wherein determining the geometric information for the at least one component of the current point based on the first geometric information ([0027] Geometric information of any point may be referred to as three-dimensional coordinates (x, y, z) of the point, and may include coordinates of the point on each coordinate axis of the three-dimensional coordinate system, that is, coordinate x of an X axis, coordinate y of a Y axis, and coordinate z of a Z axis. The attribute information of any point may include at least one of the following: color information, material information, and laser reflection intensity information (which may also be referred to as reflectivity). Each point in the point cloud data may have the same quantity of attribute information, [0063] and [0066] three dimensional coordinates of the current to be decoded point) comprises: determining the first geometric information as the geometric information of the current point ([0063] That geometric information of the current to-be-decoded point is the same as geometric information of the preceding point may mean that: Three-dimensional coordinates of the current to-be-decoded point are the same as three-dimensional coordinates of the preceding point, that is, the current to-be-decoded point is overlapped with the preceding point in three-dimensional space, so the three-dimensional coordinates are components of the first geometric information); or
determining the geometric information for the at least one component of the current point based on the first geometric information ([0027] Geometric information of any point may be referred to as three-dimensional coordinates (x, y, z) of the point, and may include coordinates of the point on each coordinate axis of the three-dimensional coordinate system, that is, coordinate x of an X axis, coordinate y of a Y axis, and coordinate z of a Z axis. The attribute information of any point may include at least one of the following: color information, material information, and laser reflection intensity information (which may also be referred to as reflectivity). Each point in the point cloud data may have the same quantity of attribute information, [0063] and [0066] three dimensional coordinates of the current to be decoded point) comprises:
determining geometric information of the first geometric information for an i-th component as geometric information of the current point for the i-th component ([0033] coordinates); and
determining a decoding mode used for geometric information of the current point for a j-th component ([0033] geometric predictive tree coding (predictive tree); [0045], [0083] and [0084] decoding mode), and
decoding the geometric information of the current point for the j-th component based on the decoding mode ([0044] (3) Point cloud decoding. Point cloud decoding is a process of decoding a compressed code stream of point cloud data to reconstruct point cloud data. In an example, it may be a process of reconstructing geometric information and attribute information of each point in the point cloud data based on a geometric bitstream and an attribute bitstream in a compressed code stream);
wherein in a case where the point cloud is a non-lidar point cloud, the i-th component is an X- coordinate component, a Y-coordinate component or a Z-coordinate component, and the j-th component is an X-coordinate component, a Y-coordinate component or a Z-coordinate component; in a case where the point cloud is a lidar point cloud, the i-th component is an X-coordinate component, a Y-coordinate component, a laser ray index or a geometric residual of a Z-coordinate, and the j-th component is an X- coordinate component, a Y-coordinate component, a laser ray index or a geometric residual of a Z- coordinate; and the i-th component is different from the j-th component ([0027]Geometric information of any point may be referred to as three-dimensional coordinates (x, y, z) of the point, and may include coordinates of the point on each coordinate axis of the three-dimensional coordinate system, that is, coordinate x of an X axis, coordinate y of a Y axis, and coordinate z of a Z axis)
Regarding claims 18 and 20, Zhu teaches a non-transitory computer-readable storage medium, wherein the non-transitory computer- readable storage medium is configured to store a computer program and a bitstream, and the computer program enables a computer to perform the following method ([0009] to [0011]), to generate the bitstream:
determining an encoding mode ([0192] encoding modes) of a current point in a node ([0032]-[0033] node and sub-nodes, [0242] each to be encoded point including a current point), and
in a case where the encoding mode of the current point is a skip encode mode (skipCodeMode) ([0243] skipping a current to-be-encoded point in a case that the current to-be-encoded point is a repeated point, so a skipping a current to be encoded point would obviously be considered as a skipCodeMode), skipping encoding of geometric information of the current point ([0067] repeated point to be skipping encoded point, [0243] skipping a current to be encoded point and the current to-be-encoded point is a repeated point meaning that geometric information of the current to-be-encoded point is the same as geometric information of any preceding point of the current to-be-encoded point).
It is noted that Zhu is silent about the current point in a current node, wherein the current node is a node to be decoded in a current picture to be encoded.
Zhang teaches the current point in in a current node ([0034] to [0036] each point that includes the current point in the current node), wherein the current node is a node to be encoded in a current picture to be encoded ([0123] other parameters that need to be coded, such as one of information among a quantity of child nodes of the current node, a prediction mode for the current node and other information, are used as to-be-coded information, [0125] for the to-be-coded information of each node, first, the quantity of child nodes of the current node needs to be coded, and second, the prediction mode for the) current node, the predicted residual (r.sub.r,r.sub.j,r.sub.i) the predicted residual (r.sub.x,r.sub.y,r.sub.z) respectively corresponding to the current node, and the predicted residual {circumflex over (n)} of the points that need to be skipped are coded).
Taking the teachings of Zhu and Yang together as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the current node to be encoded of Yang into the prediction points of Zhu to reduce geometric structural distortion of a model as much as possible, thereby improving geometry coding efficiency.
Regarding claim 19, Zhu teaches the method according to claim 18, Zhu further teaches wherein determining the encoding mode of the current point in the current node comprises: determining whether the current node meets a start condition of the skipCodeMode ([0096] that the target point cloud group meets the transform condition may include any one of the following: A quantity of points included in the target point cloud group meets a quantity condition and distribution of the reconstruction residual information of each point in the target point cloud group meets a distribution condition; [0194] when the target point cloud group meets a transform condition, transform processing may be performed on the prediction residual information of each point in the target point cloud group); and determining the encoding mode of the current point based on whether the current node meets the start condition of the skipCodeMode ([0192] distribution of the prediction residual information of each point in the target point cloud group meets a distribution condition, for example, a difference between maximum prediction residual information and minimum prediction residual information in the prediction residual information of each point in the target point cloud group is less than or equal to a distribution threshold, and a variance of the prediction residual information of each point in the target point cloud group is less than or equal to a variance threshold; [0194] when the target point cloud group meets a transform condition, transform processing may be performed on the prediction residual information of each point in the target point cloud group; [0260] for encoding modes).
Allowable Subject Matter
Claims 4 and 6-14 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ramansubramonian et al. (US 12568245 B2) discloses the encoder and the decoder, and n(j) is the number of skipped points which may be explicitly signaled in the bitstream or may be inferred from the context based on a deterministic strategy applied by both G-PCC encoder 200 and G-PCC decoder 300.
Wan et al. (US 20230386089 A1) discloses a decoder decodes a bitstream, and determines a mode parameter; in response to the mode parameter indicating to use a spatial scalability mode, the decoder determines geometric center coordinates of a current node, and determines, in the point cloud, geometric center coordinates of neighbouring nodes of the current node based on the geometric center coordinates of the current mode.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TUNG T VO whose telephone number is (571)272-7340. The examiner can normally be reached Monday-Friday 6:30 AM - 5:00 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, Brian Pendleton can be reached at 571-272-7527. 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.
TUNG T. VO
Primary Examiner
Art Unit 2425
/TUNG T VO/Primary Examiner, Art Unit 2425
