Blackberry Corporation

Apple Inc.

2236008 Ontario Limited

Velos Media, LLC

British Broadcasting Corporation

Malikie Innovations Limited

David Flynn

Sébastien Lasserre

Khaled Mammou

Alexandros Michael Tourapis

Dake He

Gaëlle Christine Martin-Cocher

Nguyen Nguyen

Marta Mrak

Andrea Gabriellini

Zhenzhen Gao

Jungsun Kim

Fabrice A Robinet

Jing Wang

Thomas Davies

Nikola Sprljan

Methods and devices for encoding a point cloud. More than one frame of reference is identified and a transform defines the relative motion of a second frame of reference to a first frame of reference. The space is segmented into regions and each region is associated with one of the frames of reference. Local motion vectors within a region are expressed relative to the frame of reference associated with that region. Occupancy of the bitstream is entropy encoded based on predictions determined using the location motion vectors and the transform associated with the attached frame of reference.

Predictive coding of point clouds using multiple frames of references

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.

In-tree geometry quantization of point clouds

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.

Predictive coding for point cloud compression

Methods and devices for encoding a point cloud. A current node associated with a sub-volume is split into further sub-volumes, each further sub-volume corresponding to a child node of the current node, and, at the encoder, an occupancy pattern is determined for the current node based on occupancy status of the child nodes. A probability distribution is selected from among a plurality of probability distributions based on occupancy data for a plurality of nodes neighbouring the current node. The encoder entropy encodes the occupancy pattern based on the selected probability distribution to produce encoded data for the bitstream and updates the selected probability distribution. The decoder makes the same selection based on occupancy data for neighbouring nodes and entropy decodes the bitstream to reconstruct the occupancy pattern.

Methods and devices for entropy coding point clouds

Methods and devices for encoding a point cloud. A bit sequence signaling an occupancy pattern for sub-volumes of a volume is coded using binary entropy coding. Contexts may be based on neighbour configuration and a partial sequence of previously-coded bits of the bit sequence. A determination is made as to whether to apply a context reduction operation and, if so, the operation reduces the number of available contexts. Example context reduction operations include reducing neighbour configurations based on shielding by sub-volumes associated with previously-coded bits, special handling for empty neighbour configurations, and statistics-based context consolidation.

Methods and devices for binary entropy coding of point clouds

Methods and devices for coding point clouds using direct coding mode to code coordinates of a point within a sub-volume associated with a current node instead of a pattern of occupancy for child nodes. Eligibility for use of direct coding is based on occupancy data from another node. If eligible, then a flag is represented in the bitstream to signal whether direct coding is applied to points in the sub-volume or not.

Methods and devices using direct coding in point cloud compression

An exemplary system receives first data representing one or more buildings, and generates second data representing the one or more buildings. Generating the second data includes, for each of the one or more buildings: (i) determining, based on the first data, a plurality of first edges defining an exterior surface of at least a portion of the building, where the first edges interconnect at a plurality of first points, (ii) encoding, in the second data, information corresponding to the quantity of the first points, (iii) encoding, in the second data, an absolute position of one of the first points, and (iv) for each of the remaining first points, encoding, in the second data, a position of that first point relative to a position of at least another one of the first points. The system outputs the second data.

Encoding and decoding map data

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.

Block-based predictive coding for point cloud compression

A system comprises an encoder configured to entropy encode a bitstream comprising both compressible and non-compressible symbols. The encoder parses the bitstream into a compressible symbol sub-stream and a non-compressible sub-stream. The non-compressible symbol sub-stream bypass an entropy encoding component of the encoder while the compressible symbol sub-stream is entropy encoded. When a quantity of bytes of entropy encoded symbols and bypass symbols is accumulated a chunk of fixed or known size is formed using the accumulated entropy encoded symbol bytes and the bypass bytes without waiting on the full bitstream to be processed by the encoder. In a complementary manner, a decoder reconstructs the bitstream from the packets or chunks.

Low-latency encoding using a bypass sub-stream and an entropy encoded sub-stream

A search space for performing nearest neighbor searches for encoding point cloud data may be trimmed. Ranges of a space filling curve may be used to identify search space to exclude or reuse, instead of generating nearest neighbor search results for at least some of the points of a point cloud located within some of the ranges of the space filling curve. Additionally, neighboring voxels may be searched to identify any neighboring points missed during the trimmed search based on the ranges of the space filling curve.

Trimming search space for nearest neighbor determinations in point cloud compression

An encoder is configured to compress point cloud geometry information using an octree/predictive tree combination geometric compression technique that embeds predictive trees in leaf nodes of an octree instead of encoding additional octree occupancy symbols for the leaf nodes. Alternatively an encoder may be configured to embed octrees in leaf nodes of a predictive tree structure. Similarly a decoder is configured to generate a reconstructed three-dimensional geometry from a bit stream including combined octree and predictive tree encoding information.

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Darmstadt, Germany

David Flynn