Source coding for transmission of reconstructed dynamic geometry: a rate-distortion-complexity analysis of different approaches

Abstract

Live 3D reconstruction of a human as a 3D mesh with commodity electronics is becoming a reality. Immersive applications (i.e. cloud gaming, tele-presence) benefit from effective transmission of such content over a bandwidth limited link. In this paper we outline different approaches for compressing live reconstructed mesh geometry based on distributing mesh reconstruction functions between sender and receiver. We evaluate rate-performance-complexity of different configurations. First, we investigate 3D mesh compression methods (i.e. dynamic/static) from MPEG-4. Second, we evaluate the option of using octree based point cloud compression and receiver side surface reconstruction.

Emerging MPEG Standards for Point Cloud Compression

“…Following several experiments and evaluations of techniques available for immersive media applications, it was found that point clouds were particularly suitable for these kinds of applications. Point cloud data scored well in experiments comparing visual quality, bitrate, and compression performance as well as computational complexity [38]. In addition, other use cases were introduced such as free viewpoint broadcasting and 3D scans produced by mobile mapping systems.…”