18052803. Point Cloud Attribute Transfer Algorithm simplified abstract (Apple Inc.)

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Point Cloud Attribute Transfer Algorithm

Organization Name

Apple Inc.

Inventor(s)

Khaled Mammou of Danville CA (US)

Yeping Su of Cupertino CA (US)

Alexandros Tourapis of Los Gatos CA (US)

Jungsun Kim of San Jose CA (US)

Valery G. Valentin of San Jose CA (US)

Fabrice A. Robinet of Sunnyvale CA (US)

Point Cloud Attribute Transfer Algorithm - A simplified explanation of the abstract

This abstract first appeared for US patent application 18052803 titled 'Point Cloud Attribute Transfer Algorithm

Simplified Explanation

The patent application describes a system that can compress and decompress attribute and spatial information for a point cloud. It also includes a point cloud attribute transfer algorithm to determine distortion between an original point cloud and a reconstructed version.

  • The system includes an encoder and a decoder to compress and decompress attribute and spatial information for a point cloud.
  • A point cloud attribute transfer algorithm is used to calculate distortion between an original point cloud and a reconstructed point cloud.
  • The algorithm also helps in selecting attribute values for a reconstructed point cloud to minimize distortion with the original point cloud.

Potential Applications

  • This technology can be used in various fields that deal with point cloud data, such as 3D modeling, virtual reality, and augmented reality.
  • It can be applied in industries like architecture, construction, and engineering for efficient storage and transmission of large point cloud datasets.
  • The system can also be used in autonomous vehicles for processing and analyzing LiDAR data.

Problems Solved

  • Compressing and decompressing attribute and spatial information for point clouds can be computationally intensive and time-consuming. This technology provides an efficient solution to this problem.
  • The point cloud attribute transfer algorithm helps in accurately reconstructing point clouds while minimizing distortion, which is crucial for applications that rely on precise 3D data.

Benefits

  • The system allows for efficient compression and decompression of point cloud data, reducing storage requirements and transmission bandwidth.
  • The point cloud attribute transfer algorithm ensures accurate reconstruction of point clouds, maintaining the fidelity of the original data.
  • By minimizing distortion, this technology improves the quality and reliability of point cloud data, enabling more accurate analysis and decision-making.


Original Abstract Submitted

A system comprises an encoder configured to compress attribute information and/or spatial for a point cloud and/or a decoder configured to decompress compressed attribute and/or spatial information for the point cloud. A point cloud attribute transfer algorithm may be used to determine distortion between an original point cloud and a reconstructed point cloud. Additionally, the point cloud attribute transfer algorithm may be used to select attribute values for a reconstructed point cloud such that distortion between an original point cloud and a reconstructed version of the original point cloud is minimized.

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