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 Arguments
Applicant’s arguments with respect to claim(s) 1-19 have been considered but are not persuasive. As shown in the updated rejection below Chou, paragraphs 62 and 84 show encoding/decoding by sequentially encoding each component(color channel).
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-2,4-7,9-13 and 15-19 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Chou (PGPub 2017/0347122) in light of the evidentiary reference Malvar (“Adaptive Run-Length / Golomb-Rice Encoding of Quantized Generalized Gaussian Sources with Unknown Statistics”) in view of Mammou (PGPub 2019/0080483)
Chou discloses 1. (Currently Amended) A method of encoding point cloud data, the method comprising:
encoding geometry data of the point cloud data; (Chou, Fig. 3A, “[0062] In the input buffer (310), the point cloud data (305) includes geometry data (312) for points as well as attributes (314) of occupied points. The geometry data (312) includes indicators of which of the points of the point cloud data (305) are occupied (that is, have at least one attribute).”)
encoding attribute data of the point cloud data based on the geometry data; and (Chou, Fig. 3A, “[0062] In the input buffer (310), the point cloud data (305) includes geometry data (312) for points as well as attributes (314) of occupied points. The geometry data (312) includes indicators of which of the points of the point cloud data (305) are occupied (that is, have at least one attribute).”)
transmitting the encoded geometry data, the encoded attribute data, and signaling data, (Chou, Fig. 3A, “[0078] The output buffer (392) is memory configured to receive and store the encoded data (395). The encoded data (395) that is aggregated in the output buffer (390) can also include metadata relating to the encoded data. The encoded data can be further processed by a channel encoder (not shown), which can implement one or more media system multiplexing protocols or transport protocols. The channel encoder provides output to a channel (not shown), which represents storage, a communications connection, or another channel for the output.”, see also paragraph 71, “The entropy coder(s) (380) pass the results of the entropy coding to the multiplexer (390), which formats the coded transform coefficients and other data to be part of the encoded data (395) for output. When the entropy coder(s) (380) use parameters to adapt entropy coding (e.g., estimates of distribution of quantized transform coefficients for buckets, as described in section V.E), the entropy coder(s) (380) also code the parameters and pass them to the multiplexer (390), which formats the coded parameters to be part of the encoded data (395).”)
wherein the attribute data includes one or more attributes, wherein one or more attributes is a color attribute wherein the color attribute is comprised of a plurality of components, (Chou, Fig. 3A, “[0062] In the input buffer (310), the point cloud data (305) includes geometry data (312) for points as well as attributes (314) of occupied points. The geometry data (312) includes indicators of which of the points of the point cloud data (305) are occupied (that is, have at least one attribute).”)
wherein a zero-run length coding is sequentially applied to each component of the attribute, and (Chou, Fig. 3A,” [0071] The entropy coder(s) (380) entropy code the quantized transform coefficients. When entropy coding the quantized transform coefficients, the entropy coder(s) (380) can use arithmetic coding, run-length Golomb-Rice coding, or some other type of entropy coding (e.g., Exponential-Golomb coding, variable length coding, dictionary coding). In particular, the entropy coder(s) (380) can apply one of the variations of adaptive entropy coding described in section V.E. Alternatively, the entropy coder(s) (380) apply some other form of adaptive or non-adaptive entropy coding to the quantized transform coefficients. The entropy coder(s) (380) can also encode general control data, QP values, and other side information (e.g., mode decisions, parameter choices).”)(Chou“ [0064] In general, a volumetric element, or voxel, is a set of one or more collocated attributes for a location in 3D space. For purposes of encoding, attributes can be grouped on a voxel-by-voxel basis. Or, to simplify implementation, attributes can be grouped for encoding on an attribute-by-attribute basis (e.g., encoding a first component plane for luma (Y) sample values for points of the frame, then encoding a second component plane for first chroma (U) sample values for points of the frame, then encoding a third component plane for second chroma (V) sample values for points of the frame, and so on). Typically, the geometry data (312) is the same for all attributes of a point cloud frame—each occupied point has values for the same set of attributes. Alternatively, however, different occupied points can have different sets of attributes.”)
wherein the signaling data includes information for identifying the one or more attributes. (Chou, paragraph 71, “to the quantized transform coefficients. The entropy coder(s) (380) can also encode general control data, QP values, and other side information (e.g., mode decisions, parameter choices)”)
Chou discloses run-length Golumb-rice coding, which inherently uses zero-run-length coding, as evidenced by Malvar (“Adaptive Run-Length / Golomb-Rice Encoding of Quantized Generalized Gaussian Sources with Unknown Statistics”) discloses details of the run-length encoding which is:
If a long run of zeros is encountered, zero-run-length encoding would be used. If the data has a more variable distribution, Golomb-Rice coding would be employed, as evidenced by the original paper shown below.
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Chou discloses 2. (Currently Amended) The method of The method of wherein the zero-run length coding is included in entropy coding performed on an entropy coding unit,(Chou, Fig. 3A, paragraph 71) and wherein the entropy coding unit is determined based on a tree structure generated based on reconstructed geometry data, based on a Morton code, or based on a level of detail (LoD). (Chou, Fig. 3a, “Octtree”)
Chou discloses 4. (Currently Amended) The method of claim 2, wherein the entropy coding further comprises performing arithmetic coding on the color attribute. (Chou, Fig. 3A, paragraph 71, “ the entropy coder(s) (380) can use arithmetic coding”)
Chou discloses 5. (Currently Amended) The method of claim 2, wherein the signaling data further comprises information related to the entropy coding. (Chou, paragraph 71, “to the quantized transform coefficients. The entropy coder(s) (380) can also encode general control data, QP values, and other side information (e.g., mode decisions, parameter choices)”)
Claims 6-7, 9-10 are rejected under similar grounds as claims 1-2 and 4-5, respectively.
Chou discloses 11. (Currently Amended) A method of decoding point cloud data, the method comprising:
receiving geometry data, attribute data, and signaling data; decoding the geometry data based on the signaling data ; and (Chou, Fig. 4a, “[0083] In the input buffer (492), the encoded data (495) includes encoded data for geometry data (412) as well as encoded data for attributes (414) of occupied points. The geometry data (412) includes indicators of which of the points of the reconstructed point cloud data (405) are occupied (that is, have at least one attribute). For example, for each of the points, a flag value indicates whether or not the point is occupied. An occupied point has one or more attributes (414) in the reconstructed point cloud data (405). The attributes (414) associated with occupied points depend on implementation (e.g., data produced by capture components, data processed by rendering components). For example, the attribute(s) for an occupied point can include: (1) one or more sample values each defining, at least in part, a color associated with the occupied point (e.g., YUV sample values, RGB sample values, or sample values in some other color space); (2) an opacity value defining, at least in part, an opacity associated with the occupied point; (3) a specularity value defining, at least in part, a specularity coefficient associated with the occupied point; (4) one or more surface normal values defining, at least in part, direction of a flat surface associated with the occupied point; (5) a light field defining, at least in part, a set of light rays passing through or reflected from the occupied point; and/or (6) a motion vector defining, at least in part, motion associated with the occupied point. Alternatively, attribute(s) for an occupied point include other and/or additional types of information. For decoding with the decoder (402) of FIG. 4b, the transform value(s) for an occupied point can also include: (7) one or more sample values each defining, at least in part, a residual associated with the occupied point.” )
decoding the attribute data based on the signaling data and the decoded geometry data;(Chou, “[0087] The entropy decoder(s) (480) entropy decode the quantized transform coefficients. When entropy decoding the quantized transform coefficients, the entropy decoder(s) (480) can use arithmetic decoding, run-length Golomb-Rice decoding, or some other type of entropy decoding (e.g., Exponential-Golomb decoding, variable length decoding, dictionary decoding). In particular, the entropy decoder(s) (480) can apply one of the variations of adaptive entropy decoding described in section V.E. Alternatively, the entropy decoder(s) (480) apply some other form of adaptive or non-adaptive entropy decoding to the quantized transform coefficients. The entropy decoder(s) (480) can also decode general control data, QP values, and other side information (e.g., mode decisions, parameter choices). The entropy decoder(s) (480) can use different decoding techniques for different kinds of information, and they can apply multiple techniques in combination. When the entropy decoder(s) (480) use parameters to adapt entropy decoding (e.g., estimates of distribution of quantized transform coefficients for buckets, as described in section V.E), the entropy decoder(s) (480) also decode the parameters before decoding the quantized transform coefficients.”)
,wherein the attribute data includes one or more attributes, wherein one of the one or more attributes is a color attribute, wherein the color attribute is comprised of a plurality of components, (Chou, Fig. 4a, “[0083] In the input buffer (492), the encoded data (495) includes encoded data for geometry data (412) as well as encoded data for attributes (414) of occupied points. The geometry data (412) includes indicators of which of the points of the reconstructed point cloud data (405) are occupied (that is, have at least one attribute). For example, for each of the points, a flag value indicates whether or not the point is occupied. An occupied point has one or more attributes (414) in the reconstructed point cloud data (405). The attributes (414) associated with occupied points depend on implementation (e.g., data produced by capture components, data processed by rendering components). For example, the attribute(s) for an occupied point can include: (1) one or more sample values each defining, at least in part, a color associated with the occupied point (e.g., YUV sample values, RGB sample values, or sample values in some other color space); (2) an opacity value defining, at least in part, an opacity associated with the occupied point; (3) a specularity value defining, at least in part, a specularity coefficient associated with the occupied point; (4) one or more surface normal values defining, at least in part, direction of a flat surface associated with the occupied point; (5) a light field defining, at least in part, a set of light rays passing through or reflected from the occupied point; and/or (6) a motion vector defining, at least in part, motion associated with the occupied point. Alternatively, attribute(s) for an occupied point include other and/or additional types of information. For decoding with the decoder (402) of FIG. 4b, the transform value(s) for an occupied point can also include: (7) one or more sample values each defining, at least in part, a residual associated with the occupied point.” )
wherein a zero-run length decoding is sequentially applied to each component of the color attribute, and ;(Chou, “0084] For purposes of decoding, attributes can be grouped on a voxel-by-voxel basis. Or, to simplify implementation, attributes can be grouped for decoding on an attribute-by-attribute basis (e.g., decoding a first component plane for luma (Y) sample values for points of the frame, then decoding a second component plane for first chroma (U) sample values for points of the frame, then decoding a third component plane for second chroma (V) sample values for points of the frame, and so on). ”;“[0087] The entropy decoder(s) (480) entropy decode the quantized transform coefficients. When entropy decoding the quantized transform coefficients, the entropy decoder(s) (480) can use arithmetic decoding, run-length Golomb-Rice decoding, or some other type of entropy decoding (e.g., Exponential-Golomb decoding, variable length decoding, dictionary decoding). In particular, the entropy decoder(s) (480) can apply one of the variations of adaptive entropy decoding described in section V.E. Alternatively, the entropy decoder(s) (480) apply some other form of adaptive or non-adaptive entropy decoding to the quantized transform coefficients. The entropy decoder(s) (480) can also decode general control data, QP values, and other side information (e.g., mode decisions, parameter choices). The entropy decoder(s) (480) can use different decoding techniques for different kinds of information, and they can apply multiple techniques in combination. When the entropy decoder(s) (480) use parameters to adapt entropy decoding (e.g., estimates of distribution of quantized transform coefficients for buckets, as described in section V.E), the entropy decoder(s) (480) also decode the parameters before decoding the quantized transform coefficients.”)
wherein the signaling data includes information for identifying the attribute. (Chou, paragraph 71, “to the quantized transform coefficients. The entropy coder(s) (380) can also encode general control data, QP values, and other side information (e.g., mode decisions, parameter choices)”)
Chou discloses 12. (Currently Amended) The method of The method of wherein the zero-run length decoding is included in entropy decoding performed on an entropy coding unit, and wherein the signaling data further comprises information related to the entropy decoding. (Chou, “[0087] The entropy decoder(s) (480) entropy decode the quantized transform coefficients. When entropy decoding the quantized transform coefficients, the entropy decoder(s) (480) can use arithmetic decoding, run-length Golomb-Rice decoding, or some other type of entropy decoding (e.g., Exponential-Golomb decoding, variable length decoding, dictionary decoding). In particular, the entropy decoder(s) (480) can apply one of the variations of adaptive entropy decoding described in section V.E. Alternatively, the entropy decoder(s) (480) apply some other form of adaptive or non-adaptive entropy decoding to the quantized transform coefficients. The entropy decoder(s) (480) can also decode general control data, QP values, and other side information (e.g., mode decisions, parameter choices). The entropy decoder(s) (480) can use different decoding techniques for different kinds of information, and they can apply multiple techniques in combination. When the entropy decoder(s) (480) use parameters to adapt entropy decoding (e.g., estimates of distribution of quantized transform coefficients for buckets, as described in section V.E), the entropy decoder(s) (480) also decode the parameters before decoding the quantized transform coefficients.”)
Chou discloses 13. (Original) The method of The method of wherein the entropy coding unit is acquired based on the signaling data, and wherein the acquired entropy coding unit is based on a tree structure generated based on reconstructed geometry data, based on a Morton code, or based on a level of detail (LoD). (Chou, Fig.4a, “Octtree decoder”)
Chou discloses 15. (Currently Amended) The method of claim 12, wherein the entropy decoding further comprises: performing arithmetic decoding on the attribute. (Chou, “[0087] The entropy decoder(s) (480) entropy decode the quantized transform coefficients. When entropy decoding the quantized transform coefficients, the entropy decoder(s) (480) can use arithmetic decoding, run-length Golomb-Rice decoding, or some other type of entropy decoding (e.g., Exponential-Golomb decoding, variable length decoding, dictionary decoding). In particular, the entropy decoder(s) (480) can apply one of the variations of adaptive entropy decoding described in section V.E. Alternatively, the entropy decoder(s) (480) apply some other form of adaptive or non-adaptive entropy decoding to the quantized transform coefficients. The entropy decoder(s) (480) can also decode general control data, QP values, and other side information (e.g., mode decisions, parameter choices). The entropy decoder(s) (480) can use different decoding techniques for different kinds of information, and they can apply multiple techniques in combination. When the entropy decoder(s) (480) use parameters to adapt entropy decoding (e.g., estimates of distribution of quantized transform coefficients for buckets, as described in section V.E), the entropy decoder(s) (480) also decode the parameters before decoding the quantized transform coefficients.”)
Claims 16-19 are rejected under similar grounds as claims 11-13 and 15.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/GANDHI THIRUGNANAM/ Primary Examiner, Art Unit 2672