Point-set compression through BSP quantization A. Bordignon, T. Lewiner, H. Lopes, G. Tavares and R. Castro Departamento de Matemática – PUC-Rio.

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Presentation transcript:

Point-set compression through BSP quantization A. Bordignon, T. Lewiner, H. Lopes, G. Tavares and R. Castro Departamento de Matemática – PUC-Rio

2 /22 Point sets

3 /22 Compression

4 /22 Contributions Geometry compression with geometry instead of combinatorics BSP quantization Progressive compression 15% improvements in compression ratios

5 /22 Overview  Tree-based compression  Cost repartition  BSP generation  Adaptative quantization  Results

6 /22 Tree-based compression Recursive subdivision Ambient space combinatorics Point position RBLB LTRT RBLB LTRT RBLB LTRT LB RT LT

7 /22 Subdivision symbols

8 /22 Emptyness symbols

9 /22 Counting symbols

10 /22 Cost repartition count emptyness

11 /22 Previous blending

12 /22 Binary Space Partition Bet:  much more information  better distributed

13 /22 BSP construction Adapted to local statistic of points

14 /22 BSP compression Cut planes codes: Euler angles Subdivision codes: counting symbols

15 /22 Angles of the cut planes Euler angles

16 /22 Quantization a ≈0.5 φ ≈ 0 ψ ≈ 0

17 /22 Small cells guarantee 0 bit quantization:  middle orthogonal cut  regular cut to reduce the cell size 10 bits quantization 5 bits quantization 0 bit quantization

18 /22 Adaptation

19 /22 Compression Ratios EmptyCount Blend

20 /22 Progressive (bpv = bit per vertex) 0.33 bpv 1.30 bpv 4.06 bpv 8.52 bpv bpv

21 /22 For now... and next Won the bet:  geometric symbols  15% improvement in compression ratio Won more:  fast, adapted BSP construction  explicit BSP cell with a local frame Next bet?  Improve progressivity  Progressive GEncode

Thank you for your attention!