2016/06/15 by Rachida Amjoun, Amjoun, Rachida, Wolfgang Straßer +1
Computer Science · #Advanced Vision and Imaging #Animation #Computer Graphics and Visualization Techniques #Computeranimation (swd: 4199710-4) #Computergraphik (swd: 4010450-3) #DCT #Informatik (DDC 004) #Rendering (swd: 4219666-8) #Video Coding and Compression Technologies #animated mesh compression #clustering #local coordinate frame #predictive coding
paper · doi:10.20385/1860-2037/5.2008.6
openalex publication_date 2024/11/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/01
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.