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
http://nbn-resolving.de/urn:nbn:de:0009-6-14446
amjoun2008