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Point cloud compression framework for the web

: Renault, S.; Ebner, T.; Feldmann, I.; Schreer, O.


Verly, J.G. ; Institute of Electrical and Electronics Engineers -IEEE-; IEEE Signal Processing Society:
International Conference on 3D Imaging, IC3D 2016. Proceedings : 13-14 December 2016, Liège, Belgium
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-5090-5743-6
ISBN: 978-1-5090-5742-9
ISBN: 978-1-5090-5744-3
ISBN: 1-5090-5744-7
International Conference on 3D Imaging (IC3D) <6, 2016, Liège>
European Commission EC
FP7-ICT; 610691; BRIDGET
Fraunhofer HHI ()

This work is dedicated to the compression of 3D point clouds in order to allow an efficient and quick transmission of point cloud datasets (PCD) for visualization over the internet. Standard methods include quantization of vectors or cloud simplification via octree structures. While a quantization into a bit representation will transform vectors in discrete positions, we added octree structures for a fixed level for re-indexing the quantized points relative to the individual local position of the subdivisions. Each subdivision multiplies the resolution of one coordinate by two, by adding a "virtual" bit. This bit can be then removed from the quantization bytes. So the combination of quantization and fixed octree structures decreases the amount of needed quantization bits without losing resolution. On the contrary, it is possible to increase the resolution of a PCD by adding the "virtual" bit to the quantized data without significantly changing the size of the dataset. We demonstrated the feasibility of this technique for the web by developing a lightweight framework, running in a browser-based environment.