Efficient Compression of 3D Models

The paper “Compressed sensing for efficient encoding of dense 3D Meshes using model based Bayesian learning” accepted for publication in the IEEE Transactions on Multimedia.The authors, Aris Lalos, Iason Nikolas, Evangelos Vlachos and Konstantinos Moustakas, developed a novel geometry compression scheme for 3D dense meshes, that achieves competitive compression ratios and significantly lower encoding complexity compared to the state-of-the-art approaches.