17933062. DECISION-MAKING RULES FOR ATTRIBUTE SMOOTHING simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)

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DECISION-MAKING RULES FOR ATTRIBUTE SMOOTHING

Organization Name

SAMSUNG ELECTRONICS CO., LTD.

Inventor(s)

Rajan Laxman Joshi of San Diego CA (US)

Hossein Najaf-zadeh of Allen TX (US)

Madhukar Budagavi of Plano TX (US)

DECISION-MAKING RULES FOR ATTRIBUTE SMOOTHING - A simplified explanation of the abstract

This abstract first appeared for US patent application 17933062 titled 'DECISION-MAKING RULES FOR ATTRIBUTE SMOOTHING

Simplified Explanation

The patent application describes a method for decoding a point cloud, which is a collection of 3D points representing the surface of an object or environment. The method involves receiving a bitstream, which is a sequence of bits that encode the point cloud data.

  • The bitstream is decoded into multiple frames, each containing pixels that represent the points of the 3D point cloud.
  • Some of the pixels are organized into patches, which correspond to clusters of points in the point cloud.
  • An occupancy map frame is also decoded from the bitstream, which indicates which pixels in the multiple frames represent the points of the 3D point cloud.
  • The method then reconstructs the 3D point cloud using the multiple frames and the occupancy map frame.
  • The method also determines whether to perform smoothing on the reconstructed 3D point cloud based on properties of the multiple frames.
  • If smoothing is determined to be necessary, the method performs the smoothing on the 3D point cloud.

Potential Applications

  • 3D scanning and modeling: The method can be used in applications that involve capturing and reconstructing 3D objects or environments, such as in virtual reality, gaming, or architectural design.
  • Autonomous navigation: The method can be applied in autonomous vehicles or robots to create accurate 3D maps of the surroundings for navigation and obstacle avoidance.
  • Augmented reality: The method can be used to enhance augmented reality experiences by improving the quality and accuracy of the 3D models overlaid on the real world.

Problems Solved

  • Efficient decoding: The method provides a way to decode a compressed bitstream efficiently, allowing for faster processing and reconstruction of the 3D point cloud.
  • Patch-based organization: By organizing pixels into patches that correspond to clusters of points, the method improves the representation and reconstruction of the 3D point cloud.
  • Smoothing optimization: The method determines whether smoothing is necessary based on the properties of the frames, optimizing the processing and improving the quality of the reconstructed 3D point cloud.

Benefits

  • Improved accuracy: The method enhances the accuracy of the reconstructed 3D point cloud by organizing pixels into patches and considering occupancy information.
  • Efficient processing: By decoding the bitstream and performing smoothing only when necessary, the method improves the efficiency of point cloud decoding and reconstruction.
  • Versatile applications: The method can be applied in various fields, including 3D scanning, autonomous navigation, and augmented reality, providing benefits in multiple industries.


Original Abstract Submitted

A method for point cloud decoding includes receiving a bitstream. The method also includes decoding the bitstream into multiple frames that include pixels. A portion of the pixels are organized into patches and correspond to respective clusters of points of a 3D point cloud. The method further includes decoding, from the bitstream, an occupancy map frame. The occupancy map frame indicates the portion of the pixels included in the multiple frames that represent the points of the 3D point cloud. In addition, the method includes reconstructing the 3D point cloud using the multiple frames and the occupancy map frame. The method also includes determining whether to perform smoothing to the 3D point cloud based at least in part on properties of the multiple frames. Based on determining to perform the smoothing, the method includes performing the smoothing to the 3D point cloud.

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