Predictive compression of geometry, color and normal data of 3-D mesh models

Abstract

Predictive compression algorithms for geometry, color and normal data of three-dimensional (3-D) mesh models are proposed in this work. In order to eliminate redundancies in geometry data, we predict each vertex position by exploiting the position and angle information in neighboring triangles. To compress color data, we propose a mapping table scheme that compresses frequently recurring colors efficiently. For normal data, we propose an average predictor and a 6-4 subdivision quantizer to improve coding gain. Simulation results demonstrate that the proposed algorithm provides better performance than the MPEG-4 standard for 3-D mesh model coding (3-DMC).