Abstract: A system comprises an encoder configured to compress and encode data for three-dimensional visual volumetric content. To compress the 3D visual volumetric content, a compressed mesh is generated as well as compressed attribute information. Also, texture coordinates indicating a mapping between the vertices of the mesh and the attributes are signaled. However, in some situations a resolution used for the texture coordinates and a resolution used for the attributes may differ, in which case the respective resolutions are signaled. A decoder determines how to adjust the texture coordinate to attribute value mapping to account for the differing resolutions.

Abstract: A system comprises an encoder configured to compress and encode data for a three-dimensional mesh. To compress the three-dimensional mesh, the encoder determines displacements to be applied to sub-division locations of a base mesh. The displacement values may be signaled in their own sub-bitstream, e.g., a dedicated displacement data sub-bitstream, or may be signaled, at least in part, in an atlas data sub-bitstream that includes patch data. In some embodiments, the displacements may also be signaled, at least in part, in a video sub-bitstream or in a base-mesh sub-bitstream.

Abstract: A system receives encoded data regarding a points in a point cloud. The data includes a prediction tree having a nodes generated based on spatial information regarding the points and properties of a sensor system that obtained the spatial information. A value of each node represents first spatial coordinates of a respective one of the points according to a first coordinate system, and the value of at least a first node in the prediction tree is determined based on ancestor nodes of the first node and the properties of the sensor system. The system decodes the data to determine first data, including the first spatial coordinates of at least some of the points, and quantization parameters associated with the first spatial coordinates. The system determines second data based on the first data, including second spatial coordinates of at least some of the points according to a second coordinate system.

Abstract: An example method includes receiving a plurality of points that represent a point cloud; representing a position of the point in each dimension of a three-dimensional space as a sequence of bits, where the position of the point is encoded according to a tree data structure; partitioning at least one of the sequences of bits into a first portion of bits and a second portion of bits; quantizing each of the second portions of bits according to a quantization step size, where the quantization step size is determined according to an exponential function having a quantization parameter value as an input and the quantization step size as an output; and generating a data structure representing the point cloud and including the quantized second portions of bits.

Abstract: According to an example method, a system receives first data representing a polygon mesh. The polygon mesh includes a plurality of interconnected vertices forming a plurality of triangles. The system generates second data representing the polygon mesh. Generating the second data includes traversing the vertices of the polygon mesh according to a traversal order, partitioning the plurality of triangles into a set of ordered triangle groups in accordance with the traversal order, and encoding, in the second data, the set of ordered triangle groups. The system outputs the second data. A position each of the vertices in the transversal order is determined based on (i) a number of previously encoded triangles that are incident to that vertex, and/or (ii) a sum of one or more angles formed by the previously encoded triangles that are incident to that vertex.

Abstract: An encoder encodes three-dimensional (3D) volumetric content, such as immersive media, using video encoded attribute patch images packed into a 2D atlas to communicate the attribute values for the 3D volumetric content. The encoder also uses mesh-encoded sub-meshes to communicate geometry information for portions of the 3D object or scene corresponding to the attribute patch images packed into the 2D atlas. The encoder applies decimation operations to the sub-meshes to simplify the sub-meshes before mesh encoding the sub-meshes. A distortion analysis is performed to bound the level to which the sub-meshes are simplified at the encoder. Mesh simplification at the encoder reduces the number of vertices and edges included in the sub-meshes which simplifies rendering at a decoder receiving the encoded 3D volumetric content.

Abstract: A system comprises an encoder configured to compress attribute information for a point cloud and/or a decoder configured to decompress compressed attribute information for the point cloud. Attribute values for at least one starting point are included in a compressed attribute information file and attribute correction values used to correct predicted attribute values are included in the compressed attribute information file. Attribute values are predicted based, at least in part, on attribute values of neighboring points and distances between a particular point for whom an attribute value is being predicted and the neighboring points. The predicted attribute values are compared to attribute values of a point cloud prior to compression to determine attribute correction values. A decoder follows a similar prediction process as an encoder and corrects predicted values using attribute correction values included in a compressed attribute information file.

Abstract: A system compresses and decompresses attribute information for visual volumetric content, such as a mesh representation. Attribute values are included in the visual volumetric representation, wherein at least some of the attribute values include unitary vectors, such as surface normal vectors or surface tangent vectors having a magnitude of one unit. In order to compress the attribute information the three-dimensional unit vectors are mapped into two dimensional parametric coordinates for a planar representation of a unit sphere. To reduce negative effects on compression due to distortion or discontinuities in the planar representation, mappings for compressing respective unit vectors are adaptively selected.

Abstract: A system comprises an encoder configured to compress attribute information and/or spatial for a point cloud and/or a decoder configured to decompress compressed attribute and/or spatial information for the point cloud. To compress the attribute and/or spatial information, the encoder is configured to convert a point cloud into an image based representation. Also, the decoder is configured to generate a decompressed point cloud based on an image based representation of a point cloud.

Abstract: A system comprises a prediction module configured to predict an attribute value, such as a texture coordinate, for a vertex of a triangle in a two-dimensional (2D) attribute representation based on known positions of vertices of a corresponding triangle in a three-dimensional (3D) geometric representation. In some embodiments, the prediction module adaptively selects a prediction technique between multiple available prediction techniques based on availability of vertices information in the 3D geometric representation and in the 2D attribute representation and further based on compression efficiency and distortion minimization. The prediction module enables compression of attribute information being signaled for volumetric visual content, such as a mesh with texture.

Abstract: An encoder is configured to compress point cloud information using a blocks of nodes determined from a prediction tree. A prediction tree is generated for a point cloud. Segments of the prediction tree are identified. The segments are divided into blocks that are predicted by predecessor blocks within the segments. The blocks of the prediction tree may then be encoded and may be provided for transmission to a decoder that can regenerate the point cloud from the blocks of the prediction tree.

Abstract: A system comprises an encoder configured to compress attribute information and/or spatial information for volumetric visual content and/or a decoder configured to decompress compressed attribute and/or spatial information for the volumetric visual content. The encoder is configured to convert a 3D representation of the visual volumetric content into a 2D image based representation. The encoder is further configured to scale the patch in 2D space independent of any scaling in 3D space. Auxiliary information is signaled for use in identifying 2D scaled or unscaled patches in an image frame, mapping the patches into 3D space, and adjusting for any scaling factors applied at the encoder.

Abstract: A system receives encoded data regarding a points in a point cloud. The data includes a prediction tree having a nodes generated based on spatial information regarding the points and properties of a sensor system that obtained the spatial information. A value of each node represents first spatial coordinates of a respective one of the points according to a first coordinate system, and the value of at least a first node in the prediction tree is determined based on ancestor nodes of the first node and the properties of the sensor system. The system decodes the data to determine first data, including the first spatial coordinates of at least some of the points, and quantization parameters associated with the first spatial coordinates. The system determines second data based on the first data, including second spatial coordinates of at least some of the points according to a second coordinate system.

Abstract: A system comprises an encoder configured to compress and encode data for a three-dimensional mesh. To compress the three-dimensional mesh, the encoder determines a compressed base mesh bit stream and a compressed motion bitstream. A network abstraction layer syntax defined for the compressed base mesh bit stream and the compressed motion bitstream, allows for various parameters to be defined and applied to both bit streams, such as timing information and faceIDs for faces of polygons of the mesh.

Abstract: An example method includes receiving (502) a plurality of points that represent a point cloud; representing a position of the point in each dimension of a three-dimensional space as a sequence of bits (504), where the position of the point is encoded according to a tree data structure; partitioning (506) at least one of the sequences of bits into a first portion of bits and a second portion of bits; quantizing (508) each of the second portions of bits according to a quantization step size, where the quantization step size is determined according to an exponential function having a quantization parameter value as an input and the quantization step size as an output; and generating (510) a data structure representing the point cloud and including the quantized second portions of bits.

Abstract: A system compresses and decompresses attribute information for visual volumetric content, such as a mesh representation. Attribute values are included in the visual volumetric representation, wherein at least some of the attribute values include unitary vectors, such as surface normal vectors or surface tangent vectors having a magnitude of one unit. In order to compress the attribute information the three-dimensional unit vectors are mapped into two dimensional parametric coordinates for a planar representation of a unit sphere. To reduce negative effects on compression due to distortion or discontinuities in the planar representation, mappings for compressing respective unit vectors are adaptively selected.

Abstract: A system comprises an encoder configured to compress and encode data for a three-dimensional mesh using a video encoding technique. To compress the three-dimensional mesh, the encoder determines sub-meshes and for each sub-mesh: texture patches and geometry patches. Also the encoder determines patch connectivity information and patch texture coordinates for the texture patches and geometry patches. The texture patches and geometry patches are packed into video image frames and encoded using a video codec. Additionally, the encoder determines boundary stitching information for the sub-meshes. A decoder receives a bit stream as generated by the encoder and reconstructs the three-dimensional mesh.

Abstract: Adaptive decoder-drive encoder reconfiguration techniques are described. In one example, techniques include detecting an operational condition at a consumer using a sensor, the consumer receiving a communication of digital content from an encoder; generating an adaptation instruction by the decoder based on the detecting; transmitting the adaptation instruction by the decoder for receipt by the encoder; and receiving an adapted communication of the digital content generated by the encoder, the adapted communication caused by reconfiguration of the encoder based on the adaptation instruction received from the decoder.

Abstract: A system comprises an encoder configured to compress and encode data for a three-dimensional mesh. To compress the three-dimensional mesh, the encoder determines sub-meshes and for each sub-mesh: texture patches and geometry patches. Also, the sub-meshes may be grouped into patches, patch-groups, and/or tiles. Different encoding parameters may be used for such different coding units (e.g., patches, patch-groups and/or tiles). However, the encoding parameters are adjusted for vertices that are shared between coding units to avoid introduction of artefacts. A decoder receives a bit stream as generated by the encoder and reconstructs the three-dimensional mesh.

Abstract: An encoder is configured to compress point cloud geometry information using an octree geometric compression technique that utilizes a binary arithmetic encoder, a look-ahead table, a cache, and a context selection process, wherein encoding contexts are selected based, at least in part, on neighborhood configurations. In a similar manner, a decoder is configured to decode compressed point cloud geometry information utilizing a binary arithmetic encoder, a look-ahead table, a cache, and a context selection process.