Adaptive Distance Based Point Cloud Compression

A method comprising:

• identifying a set of neighboring points greater than a first distance and less than a second distance from a point of a point cloud;
• determining whether a variability of attribute values of the neighboring points exceeds a variability threshold;
• determining respective predicted attribute values for one or more points of a sub-set of respective points of the point cloud according to:
• a first prediction procedure if the variability of the attribute values of the neighboring points is less than the threshold;
• or
• another prediction procedure if the variability of the attribute values of the neighboring points exceeds the threshold;
• determining respective attribute correction values for the one or more points of the sub-set, based on comparing the respective predicted attribute values for respective ones of the one or more points of the sub-set to the attribute information for corresponding respective points included in the point cloud prior to the point cloud being encoded;
• and
• encoding the determined attribute correction values.

A non-transitory computer-readable medium storing program instructions, that when executed by one or more processors, causes the one or more processors to:

• receive compressed attribute information for a point cloud, the compressed attribute information comprising an assigned attribute value for at least one point of the point cloud and data indicating attribute correction values for attributes of other points of the point cloud;
• predict attribute values for respective ones of the points of the point cloud, wherein to predict the attribute values for the respective ones of the points of the point cloud, the program instructions, when executed on the one or more processors, cause the one or more processors to:
• identify a set of neighboring points greater than a first distance and less than a second distance from a respective point;
• determine whether a variability of attribute values of the set of neighboring points exceeds a variability threshold;
• determine respective predicted attribute values for the respective points according to:
• a first prediction procedure if the variability of the attribute values of the neighboring points is less than the threshold;
• or
• another prediction procedure if the variability of the attribute values of the neighboring points exceeds the threshold;
• and
• apply one or more attribute correction values to the predicted attribute values to determine attribute information for a reconstructed version of the point cloud.