Compression au fil de l'eau de séquences de maillages 3D par analyse multirésolution

Nous proposons dans cette thèse deux approches de compression géométrique de maillages 3D dynamiques au fil de l eau pour analyse multirésolution. Comme première approche de compression, le codeur TWC (Temporal Wavelet Coding) est proposé, incluant une transformée en ondelettes temporelle mise en œuvre au moyen d un schéma lifting, où plusieurs schémas lifting ont été testés. Les sous-bandes de la transformée en ondelettes sont codées avec une technique basée sur une allocation binaire, permettant d obtenir les pas de quantification optimaux, selon un critère débit / distorsion. En deuxième approche de compression, le codeur appelé MCTWC (Motion Compensated Temporal Wavelet Coding) est proposé, s appuyant sur la transformée en ondelettes incluant une compensation de mouvement, un codage arithmétique des matrices de mouvement et des partitions, et un codage des sous-bandes par le codeur basé sur l allocation binaire. Une technique de segmentation automatique au sens du mouvement est proposée, consistant à regrouper dans des parties (clusters) les sommets qui suivent un mouvement affine proche, sous la condition de la minimisation de l erreur de compensation de mouvement. Une estimation / compensation du mouvement est appliquée ensuite sur chaque cluster de la partition pour obtenir une séquence compensée en mouvement par parties, sur laquelle est appliqué la transformée en ondelettes par schéma lifting.We propose in this thesis two approaches for geometric compression of 3D dynamic meshes computing on the fly multiresolution analysis. As a first compression approach, the encoder TWC (Temporal wavelet Coding) is proposed, including a temporal wavelet transforms implemented by several lifting schemes. The subbands of the wavelet transforms are encoded thanks to a bit allocation giving the optimal quantization steps, by optimizing the rate-distorstion trade-off. A second compression approach is proposed, called MCTWC (Motion Compensated Temporal Wavelet Coding). It is based on the motion compensated wavelet transform. An automatic motion-based segmentation technique is proposed using z region growing approach : the vertices that follow the same affine motion belong to a same cluster. A motion estimation / compensation is then applied to each cluster of the partition to obtain a cluster-based motion compensation sequence. Then, a wavelet-based lifting scheme is applied. Experimentally, the encoder MCTWC including motion compensation improves significantly the compression performances compared to the encoder TWC which does not include this feature. Also, compared to some state of the art encoders, the proposed coders do not depend on the geometric characteristics of the mesh sequences, permit a low computational complexity multiresolution analysis, and offer features like temporal scalability and streaming.NICE-BU Sciences (060882101) / SudocSudocFranceF

Temporal wavelet-based compression of 3D animated meshes using motion-based clustering

Abstract This paper presents an efficient compression algorithm to encode the geometry of 3D mesh sequences with fixed connectivity. The proposed approach includes a temporal scan-based wavelet transform and motion compensation of the mesh geometry. Motion estimation/compensation is performed thanks to an efficient motion-based clustering approach The motion parameters are modeled by affine transforms matrix which are coded losslessly using arithmetic coding. Simulation results show that the proposed method provides good compression performances

MOTION-BASED MESH CLUSTERING FOR MCDWT COMPRESSION OF 3D ANIMATED MESHES

We present an efficient compression algorithm for sequences of triangular meshes with fixed connectivity. Our two main contributions in this paper are: a clustering technique which regroups the vertices following the same affine motion; a geometry compensation technique based on the estimation of 3D motion parameters which are modeled by affine transform matrices. Then, a scanbased temporal discrete wavelet transform is applied on the compensated sequence, and the resulting wavelet coefficients are finally encoded by an efficient coding scheme which includes a bit allocation process. Simulation results show that our compression method provides good compression performances compared to some state of the art coders. 1