Predictive coding for point cloud compression

A device comprising:

• one or more processors;
• and
• memory storing instructions that when executed by the one or more processors, cause the one or more processors to perform operations comprising:
• receiving encoded data regarding a plurality of points in a three-dimensional point cloud, wherein the encoded data comprises:
• a prediction tree having a plurality of nodes generated based on spatial information regarding the plurality of points and one or more properties of a sensor system that obtained the spatial information,
• wherein the sensor system comprises one or more light detection and ranging (LIDAR) sensors, and wherein the one or more properties of the sensor system comprise at least one of:
• a rotational speed of one or more light emitters in the one or more LIDAR sensors,
• a physical arrangement of one or more light emitters in the one or more LIDAR sensors, or
• a pattern of emission of one or more light emitters in the one or more LIDAR sensors,
• wherein a value of each node in the prediction tree represents first spatial coordinates of a respective one of the plurality of points according to a first coordinate system, and
• wherein the value of at least a first node in the prediction tree is determined by predicting a position of a first point associated with the first node based on a value of one or more ancestor nodes of the first node and the one or more properties of the sensor system;
• decoding the encoded data to determine first data regarding the plurality of points, wherein the first data comprises:
• the first spatial coordinates of at least some of the points, and
• one or more quantization parameters associated with the first spatial coordinates;
• determining second data regarding the plurality of points based on the first data, wherein the second data comprises second spatial coordinates of at least some of the points according to a second coordinate system different from the first coordinate system;
• and
• generating a representation of the three-dimensional point cloud based on the second data.

One or more non-transitory, computer-readable storage media having instructions stored thereon, that when executed by one or more processors, cause the one or more processors to perform operations comprising:

• receiving encoded data regarding a plurality of points in a three-dimensional point cloud, wherein the encoded data comprises:
• a prediction tree having a plurality of nodes generated based on spatial information regarding the plurality of points and one or more properties of a sensor system that obtained the spatial information,
• wherein the sensor system comprises one or more light detection and ranging (LIDAR) sensors, and wherein the one or more properties of the sensor system comprise at least one of:
• a rotational speed of one or more light emitters in the one or more LIDAR sensors,
• a physical arrangement of one or more light emitters in the one or more LIDAR sensors, or
• a pattern of emission of one or more light emitters in the one or more LIDAR sensors,
• wherein a value of each node in the prediction tree represents first spatial coordinates of a respective one of the plurality of points according to a first coordinate system, and
• wherein the value of at least a first node in the prediction tree is determined by predicting a position of a first point associated with the first node based on a value of one or more ancestor nodes of the first node and the one or more properties of the sensor system;
• decoding the encoded data to determine first data regarding the plurality of points, wherein the first data comprises:
• the first spatial coordinates of at least some of the points, and
• one or more quantization parameters associated with the first spatial coordinates;
• determining second data regarding the plurality of points based on the first data, wherein the second data comprises second spatial coordinates of at least some of the points according to a second coordinate system different from the first coordinate system;
• and
• generating a representation of the three-dimensional point cloud based on the second data.