'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
Rate-distortion optimal 3D point cloud compression
is very challenging due to the irregular structure of 3D point
clouds. For a popular 3D point cloud codec that uses octrees for
geometry compression and JPEG for color compression, we first
find analytical models that describe the relationship between the
encoding parameters and the bitrate and distortion, respectively.
We then use our models to formulate the rate-distortion optimization
problem as a constrained convex optimization problem
and apply an interior point method to solve it. Experimental
results for six 3D point clouds show that our technique gives
similar results to exhaustive search at only about 1.57% of its
computational cost