Predictive-DCT Coding for 3D Mesh Sequences Compression Amjoun Rachida Strasser Wolfgang This paper proposes a new compression algorithm for dynamic 3d meshes. In such a sequence of meshes, neighboring vertices have a strong tendency to behave similarly and the degree of dependencies between their locations in two successive frames is very large which can be efficiently exploited using a combination of Predictive and DCT coders (PDCT). Our strategy gathers mesh vertices of similar motions into clusters, establish a local coordinate frame (LCF) for each cluster and encodes frame by frame and each cluster separately. The vertices of each cluster have small variation over a time relative to the LCF. Therefore, the location of each new vertex is well predicted from its location in the previous frame relative to the LCF of its cluster. The difference between the original and the predicted local coordinates are then transformed into frequency domain using DCT. The resulting DCT coefficients are quantized and compressed with entropy coding. The original sequence of meshes can be reconstructed from only a few non-zero DCT coefficients without significant loss in visual quality. Experimental results show that our strategy outperforms or comes close to other coders. Animation DCT animated mesh compression clustering local coordinate frame predictive coding 004 periodical academic journal JVRB - Journal of Virtual Reality and Broadcasting 5(2008) 6 2008 1860-2037 urn:nbn:de:0009-6-14446 10.20385/1860-2037/5.2008.6 amjoun2008