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Sujet de thèse - 2022

Representation and analysis of immersive dynamic data based on vector quantization and reinforcement learning


Période : 2022-2025

The thesis addresses the issue of representation and analysis of immersive dynamic data by using vector quantization and reinforcement learning. In the LS2N/IPI team we have already an experience in Geometric Point Cloud Compression domain by using Tree-Structured Point-Lattice Vector Quantization. We plan to extend the method for the analysis and representation of the dynamic 3D contents.

Vincent Ricordel

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