Decoding attribute values in geometry-based point cloud compression

A method for processing point cloud data, the method comprising:

• determining a first attribute value for a first point of a point cloud, wherein the first point of the point cloud is a closest already-decoded point to a current point of the point cloud;
• determining a second attribute value for a second point of the point cloud, wherein the second point of the point cloud is a second closest already-decoded point to the current point of the point cloud;
• determining a third attribute value for a third point of the point cloud, wherein the third point of the point cloud is a third closest already-decoded point to the current point of the point cloud;
• determining a fourth attribute value for a fourth point of the point cloud, wherein the fourth point of the point cloud is an already-decoded point that is further from the current point than the third point;
• determining a set of predictor candidates for an attribute value of the current point of the point cloud, wherein the current point defines an intersection of an x-axis, a y-axis, and a z-axis, wherein the x-axis, the y-axis, and the z-axis form an x-y plane, an x-z plane, and a y-z plane, wherein to determine the set of predictor candidates for the current point of the point cloud, wherein determining the set of predictor candidates comprises generating the set of predictor candidates with a subset of the first attribute value, the second attribute value, the third attribute value, and the fourth attribute value based on a comparison of a location of the second point to a location of the third point;
• and
• decoding the attribute value of the current point based on the set of predictor candidates.

A computer-readable storage medium storing instructions that when executed by one or more processors cause the one or more processor to:

• determine a first attribute value for a first point of a point cloud, wherein the first point of the point cloud is a closest already-decoded point to a current point of the point cloud;
• determine a second attribute value for a second point of the point cloud, wherein the second point of the point cloud is a second closest already-decoded point to the current point of the point cloud;
• determine a third attribute value for a third point of the point cloud, wherein the third point of the point cloud is a third closest already-decoded point to the current point of the point cloud;
• determine a fourth attribute value for a fourth point of the point cloud, wherein the fourth point of the point cloud is an already-decoded point that is either further from the current point than the third point or a same distance to the current point as the third point;
• determine a set of predictor candidates for an attribute value of the current point of the point cloud, wherein the current point defines an intersection of an x-axis, a y-axis, and a z-axis, wherein the x-axis, the y-axis, and the z-axis form an x-y plane, an x-z plane, and a y-z plane, wherein to determine the set of predictor candidates for the current point of the point cloud, the one or more processors are further configured to generate the set of predictor candidates with a subset of the first attribute value, the second attribute value, the third attribute value, and the fourth attribute value based on a comparison of a location of the second point to a location of the third point;
• and
• decode the attribute value of the current point based on the set of predictor candidates.