Presentation + Paper
6 September 2019 Point cloud compression on the basis of 3D motion estimation and compensation
Author Affiliations +
Abstract
The point cloud is a medium that visualizes various information by placing a point having a color value and a geometry value in a three-dimensional space. The point cloud uses dozens and millions of points for visualization of information, and the key point of commercialization of this point cloud video is to efficiently compress a large amount of information of point cloud and transmit it to users. Currently, MPEG V-PCC is conducting dynamic point cloud compression research using the 2D video codec, where motion estimation is conducted in terms of 2D video sequences. Thus, there is a limitation in estimating the motion in 3D point cloud contents. In this paper, we propose the method to use the 3D motion for point cloud video compression. The proposed technology achieves efficient compression rate and improves accuracy in lossy compression.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Junsik Kim, Jiheon Im, Sungryeul Rhyu, and Kyuheon Kim "Point cloud compression on the basis of 3D motion estimation and compensation", Proc. SPIE 11137, Applications of Digital Image Processing XLII, 1113719 (6 September 2019); https://doi.org/10.1117/12.2526702
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Clouds

Video

Video compression

3D video compression

Image compression

Motion estimation

3D image processing

RELATED CONTENT

A polygon soup representation for free viewpoint video
Proceedings of SPIE (February 04 2010)
Hybrid pyramidal/vector-quantized volume compression
Proceedings of SPIE (March 21 1997)
Predictive Coding of Depth Images Across Multiple Views
Proceedings of SPIE (March 05 2007)
Encoding-scaled MPEG video in compressed domain
Proceedings of SPIE (January 10 1997)

Back to Top