Apple Inc. (Cupertino, CA)

An encoder is used to compress information about the attribute of a point cloud and/or space information, and/or a coder to decompress the compressed attribute and/or space information. To compress the attribute and/or spatial information encoders are configured to convert a point cloud into an image based representation. Additionally, the decoder is designed to produce a decompressed point cloud based on an image based representation of a point cloud. The encoder is set to for projecting the point cloud to patch planes in order to reduce the size of the cloud and can support multi-layered patch planes. For example, some point clouds might have a depth, and points at different depths may be assigned to different layers of patch planes.

Technical Field

This disclosure is general in nature and relates to compression and decompression point clouds, which contain a plurality points with associated spatial information and attributes.

Description of the Related Art

Various types of sensors, like light detection and ranging (LIDAR) systems 3D-cameras, 3-D scanners and others. could capture data that indicates the position of three-dimensional points space, such as positions in the X the Y, X, and Z planes. Additionally, such systems can collect attribute information as well as spatial information for the respective points including colors (e.g. RGB values) as well as texture information, reflection attributes, intensity attributes, motion relatedattributes, modality attributes, or different attributes. In some circumstances, additional attributes may be added to the specific points, such as the time of the moment the point was captured. Points captured by such sensors can form a “pointcloud” consisting of a collection of points, each with its own with spatial information, and some or all of the attributes associated with them. A point cloud can contain thousands, hundreds of thousand millions or even more , depending on the situation. Also, in some circumstances, point clouds may be created, for instance in software, as opposed to being captured by one or several sensors. In either scenario, point clouds may include large amounts of information and can be expensive and take a long time to store and transmit.

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