%0 Journal Article %1 AS08 %A Amjoun, Rachida %A Straßer, Wolfgang %D 2008 %E Herder, Jens %J Journal of Virtual Reality and Broadcasting %K 3D_Graphics 5(2008)6 5.2008 Animated_Mesh_Compression Animation Clustering Compression Compression_Algorithm Computer_Animation Computer_Graphics DCT DiPP Digital_Peer_Publishing_Initiative Digital_Peer_Publishing_License Dynamic_3D_Meshes JVRB Journal_of_Virtual_Reality_and_Broadcasting Local_Coordinate_Frame Open_Access Peer-Reviewed Peer_Reviewed Predictive_Coding Rendering [AS08] %N 6 %T Predictive-DCT Coding for 3D Mesh Sequences Compression %V 5 %X 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.

@article{AS08, abstract = {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.}, added-at = {2009-01-13T17:09:36.000+0100}, author = {Amjoun, Rachida and Stra{\ss}er, Wolfgang}, biburl = {https://www.bibsonomy.org/bibtex/2838d7b0bd15f22d856dd7bda2f07c003/jvrb_regulski}, editor = {Herder, Jens}, interhash = {d5106ccdc5df97590f949834bfa88540}, intrahash = {838d7b0bd15f22d856dd7bda2f07c003}, journal = {Journal of Virtual Reality and Broadcasting}, keywords = {3D_Graphics 5(2008)6 5.2008 Animated_Mesh_Compression Animation Clustering Compression Compression_Algorithm Computer_Animation Computer_Graphics DCT DiPP Digital_Peer_Publishing_Initiative Digital_Peer_Publishing_License Dynamic_3D_Meshes JVRB Journal_of_Virtual_Reality_and_Broadcasting Local_Coordinate_Frame Open_Access Peer-Reviewed Peer_Reviewed Predictive_Coding Rendering [AS08]}, month = {July}, note = {{\tt urn:nbn:de:0009-6-14446,}, ISSN 1860-2037}, number = 6, timestamp = {2009-01-13T17:09:36.000+0100}, title = {Predictive-DCT Coding for 3D Mesh Sequences Compression}, volume = 5, year = 2008 }