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Point-set compression through BSP quantization

This work explores innovative methods for compressing point sets utilizing Binary Space Partition (BSP) quantization, offering up to a 15% improvement in compression ratios. It discusses the integration of geometry over combinatorial approaches to enhance data representation quality. Key techniques such as tree-based compression, adaptive quantization, and cost repartitioning are examined. Emphasizing the importance of local statistics and subdivision methods, the study provides insights into maximizing efficiency in point cloud storage and transmission while maintaining data integrity.

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Point-set compression through BSP quantization

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

  2. Point sets

  3. Compression

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

  5. Overview Tree-based compression Cost repartition BSP generation Adaptative quantization Results

  6. Tree-based compression Recursive subdivision Ambient space combinatorics Point position • LB RT LT LT RT LT RT LT RT LB RB LB RB LB RB

  7. Subdivision symbols

  8. Emptyness symbols +0 ++ ++ 0+ ++ ++ 0+

  9. Counting symbols • 005 5 4 2 1 1

  10. Cost repartition • count • emptyness

  11. Previous blending • ++ +1 1+ 11 +0 0+ 10 01

  12. Binary Space Partition Bet: much more information better distributed

  13. BSP construction Adapted to local statistic of points

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

  15. Angles of the cut planes Euler angles

  16. Quantization a ≈0.5φ≈ 0ψ≈ 0

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

  18. Adaptation

  19. Compression Ratios Empty Count Blend

  20. Progressive • (bpv = bit per vertex) • 0.33 bpv • 1.30 bpv • 4.06 bpv • 8.52 bpv • 15.35 bpv

  21. 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

  22. Thank you foryour attention! http://www.mat.puc-rio.br/~tomlew

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