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In this paper, we propose the motion recurring pattern analysis (MRPA) method for the lossless representation of a motion database at the segment level instead of the motion degree of freedom (DOF) level. First, we concatenate all the motions into a long sequence in the motion database, and we discover similar posture paths by building a matching trellis structure based on the randomized k-d tree. Second, horizontal segments of paths are suitably refined, based on a self-organizing map, to obtain the optimized segmentation for maximum compression gains. Third, by using the path as a connection agent, these segments are clustered into a forest of trees. With this forest structure, we obtain the prediction residuals (the differences between the nonroot branches and their parents), and the differences between neighboring residuals are encoded under floating-point compression. Relative to previous lossless compression methods, our approach can achieve a higher compression ratio with comparable decompression time costs.

International audience; With the recent advances in data acquisition techniques, the compression of various dynamic mesh sequence data has become an important topic in the computer graphics community. In this article, we present a new spatio-temporal segmentation-based approach for the adaptive compression of the dynamic mesh sequences. Given an input dynamic mesh sequence, we first compute an initial temporal cut to obtain a small subsequence by detecting the temporal boundary of dynamic behavior. Then, we apply a two-stage vertex clustering on the resulting subsequence to classify the vertices into groups with optimal intra-affinities. After that, we design a temporal segmentation step based on the variations of the principal components within each vertex group prior to performing a PCA-based compression. Furthermore, we apply an extra step on the lossless compression of the PCA bases and coefficients to gain more storage saving. Our approach can adaptively determine the temporal and spatial segmentation boundaries to exploit both temporal and spatial redundancies. We have conducted extensive experiments on different types of 3D mesh animations with various segmentation configurations. Our comparative studies show the advantages of our approach for the compression of 3D mesh animations.

In computer graphics, animation compression is essential for efficient storage, streaming and reproduction of animated meshes. Previous work has presented efficient techniques for compression using skinning transformations to derive the animated mesh from a reference pose. We present a pose-to-pose approach to skinning animated meshes by observing that only small deformation variations will normally occur between consecutive poses. The transformations are applied so that a new pose is derived by deforming the geometry of the previous pose, thus maintaining temporal coherence in the parameter space, reducing approximation error and facilitating forward propagated editing of arbitrary poses.

International audience; This paper presents a new compression technique for 3D dynamic meshes, referred to as FAMC - Frame-based Animated Mesh Compression, recently promoted within the MPEG-4 standard as Amendement 2 of part 16 (AFX - Animation Framework eXtension). The FAMC approach combines a model-based motion-compensation strategy with transform/predictive coding of residual errors. First, a skinning motion-compensation model is automatically derived from a frame-based representation. Subsequently, either 1) DCT/lifting wavelets or 2) layer-based predictive coding is employed to exploit remaining spatio-temporal correlations in the residual signal. Both motion model parameters and residual signal components are finally encoded by using context-based adaptive binary arithmetic coding (CABAC). The proposed FAMC encoder offers high compression performance with gains of 60% in terms of bit-rate savings relative to previous MPEG-4 technology and of 20% to 40% relative to state-of-the-art techniques. FAMC is well suited for compressing both geometric and photometric (normal vectors, colors...) attributes. In addition, FAMC also supports a rich set of functionalities including streaming, scalability (spatial, temporal and quality) and progressive transmission

The MPEG-4 standard adopted a novel technology for compression of dynamic 3D meshes with constant connectivity and time-varying geometry, referred to as FAMC - frame-based animated mesh compression. In this paper, we propose two optimizations of the FAMC approach, aiming at improving the compression efficiency. The first one is based on a PCA (principal component analysis) decomposition of the motion compensation error residuals. The second improves the bi-orthogonal (4-2) wavelet coding approach supported by the standard, by introducing an optimal bit allocation procedure, combined with an adapted quantization of wavelet coefficients. Experimental results show that both optimizations lead to significant gains in compression rate (about 20-30%) at low bitrates.

This paper presents first compression results on using the MPEG-4 BBA standard for encoding motion capture data. We first introduce a detailed description of the main compression mechanisms used in recently BBA standard: prediction, frequency transform, quantization and entropy encoder and discuss the theoretical range of encoding performances. Then we introduce an optimized BBA encoder including also a key-frame reduction mechanism and show the compression results on animation files from typical motion capture data-base. We compare the results with the ones reported in literature showing the advantages of the MPEG-4 BBA in terms of bit-rate, complexity and range control.