Back to articles
3D Data Processing and Compression
Volume: 28 | Article ID: art00005
Image
Point Cloud Compression using Depth Maps
  DOI :  10.2352/ISSN.2470-1173.2016.21.3DIPM-397  Published OnlineFebruary 2016
Abstract

In this paper we investigate the usage of depth maps as a structure to represent a point cloud. The main idea is that depth maps implicitly define a global manifold structure for the underlying surface of a point cloud. Thus, it is possible to only work on the parameter domain, and to modify the point cloud indirectly. We show that this approach simplifies local computations on the point cloud and allows using standard image processing algorithms to interact with the point cloud. We present results of the application of standard image compression algorithms applied on depth maps to compress a point cloud, and compare them with state-of-the-art techniques in point cloud compression. We also present a method to visualize point clouds in a progressive manner, using a multiresolution analysis of depth maps.

Subject Areas :
Views 18
Downloads 1
 articleview.views 18
 articleview.downloads 1
  Cite this article 

Arnaud Bletterer, Frédéric Payan, Marc Antonini, Anis Meftah, "Point Cloud Compression using Depth Mapsin Proc. IS&T Int’l. Symp. on Electronic Imaging: 3D Image Processing, Measurement (3DIPM), and Applications,  2016,  https://doi.org/10.2352/ISSN.2470-1173.2016.21.3DIPM-397

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2016
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology