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In this paper, we propose a compression scheme for animated semi-regular meshes. This scheme includes a spatio-temporal wavelet filtering to exploit the coherence both in time and space. In order to optimize the quantization of both spatial and temporal wavelet coefficients, the proposed compression scheme also includes a model-based bit allocation. The(More)
In this paper, we present a new framework to analyse and process 3D animations (defined by sequences of triangular meshes sharing the same connectivity at any frame). Our idea is to develop a spatio-temporal wavelet filtering for such data, leading to a relevant multiresolution decomposition. In geometry processing, the most efficient spatial wavelets are(More)
We propose an adaptive semi-regular remeshing algorithm for surface meshes. Our algorithm uses Voronoi tessellations during both simplification and refinement stages. During simplification, the algorithm constructs a first centroidal Voronoi tessellation of the vertices of the input mesh. The sites of the Voronoi cells are the vertices of the base mesh of(More)
In this paper, we derive a performance comparison between two training-based schemes for MIMO semi-blind channel estimation. The two schemes are the conventional superimposed training scheme and the more recently proposed data-dependent superimposed pilot scheme. For both schemes, a closed-form for the outage probability and a lower bound of the bit error(More)
In this paper, we propose an optimization of the lifted Butterfly scheme for semi-regular meshes. This optimization consists in adapting prediction and update steps at each level of resolution for a given semi-regular mesh. The motivation is the improvement of the multiresolution analysis in order to increase the compression performances of the subsequent(More)
In semi-blind channel estimation techniques, the choice of the regularizing parameter that weights the blind criterion when linearly combined to the training-based least square criterion has a great impact on channel estimation performance. If a scalar regularization is considered, it has been noted that the optimal value of the regularizing factor has no(More)
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