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3D point cloud lossy compression using quadric surfaces.

Ulfat Imdad1, Mirza Tahir Ahmed2, Muhammad Asif1

  • 1Department of Computer Science, National Textile University, Faisalabad, Pakistan.

Peerj. Computer Science
|October 29, 2021
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Summary
This summary is machine-generated.

This study introduces a new lossy compression method for 3D point cloud data using quadric surface representation. This technique efficiently reduces storage and network bandwidth for smart devices.

Keywords:
Point cloudRegistrationVirtual interest point

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Area of Science:

  • Computer Vision
  • Geometric Modeling
  • Data Compression

Background:

  • 3D sensors are increasingly common in smart devices, necessitating efficient 3D point cloud data management.
  • Existing compression techniques face challenges in balancing efficiency, storage, and bandwidth usage.

Purpose of the Study:

  • To develop a novel lossy compression technique for 3D point cloud data.
  • To reduce storage space on smart devices and minimize network bandwidth consumption.
  • To leverage geometric scene information for effective compression.

Main Methods:

  • Exploiting geometric scene information via quadric surface representation of 3D point clouds.
  • Representing point cloud regions using quadric surface coefficients and boundary conditions.
  • Storing coefficients and boundary conditions as compressed data for decompression.

Main Results:

  • The proposed technique offers efficient compression and decompression of 3D point cloud data.
  • It provides flexibility in decompressing point clouds at varying densities (dense or coarse).
  • Performance was evaluated against state-of-the-art lossless and lossy compression methods on diverse datasets.

Conclusions:

  • The novel quadric surface representation enables effective lossy compression of 3D point clouds.
  • This method significantly saves storage and bandwidth, crucial for mobile and networked applications.
  • The technique's adaptability in decompression density adds practical value for various use cases.