Recently we have proposed a coding algorithm of point cloud geometry based on a rather different approach from the popular octree representation. In our algorithm, the point cloud is decomposed in silhouettes, hence t...
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Recently we have proposed a coding algorithm of point cloud geometry based on a rather different approach from the popular octree representation. In our algorithm, the point cloud is decomposed in silhouettes, hence the name Silhouette coder, and context adaptive arithmetic coding is used to exploit redundancies within the point cloud (intra frame coding), and also using a reference point cloud (inter frame coding). In this letter we build on our previous work and propose a context selection algorithm as a pre-processing stage. With this algorithm, the point cloud is first parsed testing a large number of candidate context locations. The algorithm selects a small number of these contexts that better reflect the current point cloud, and then encode it with this choice. The proposed method further improves the results of our previous coder, Silhouette 4D, by 10%, on average, on a dynamic point cloud dataset of the JPEG Pleno, and achieves bitrates competitive with some high quality lossy coders such as the MPEG G-PCC.
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