Probability model-adaptive coding of point clouds with octree decomposition

  • Authors:

  • Kangying Cai;Wenfei Jiang;Teng Ma;Jiang Tian;Wencheng Wang;Tao Luo

  • Affiliations:

  • TechniColor R&I Beijing, and State Key Lab. of Comp. Sci., ISCAS;TechniColor R&I Beijing;TechniColor R&I Beijing, and School of Comp. Sci. and Eng., BeiHang Univ.;TechniColor R&I Beijing;State Key Lab. of Comp. Sci., ISCAS;TechniColor R&I Beijing

  • Venue:
  • SIGGRAPH Asia 2011 Posters
  • Year:
  • 2011

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Abstract

An important observation is that when compressing point clouds using Octree (OT) decomposition based compression algorithms [Peng and Kuo 2005; Huang et al. 2008], the octree nodes with only one non-empty child (single-point nodes), occur in an increasing frequency as the cell subdivision goes deeper. The commonly employed entropy codec uses a probability model which keeps updating during the coding process. However, as illustrated in Fig.1 (b), the symbol distribution keeps varying and thus the probability model trained online is seldom perfectly matched with the real statistical distribution. Thus, there is still much room left to further save the bitrates when using these codecs.