Paper Info
Title
Autofocus on Depth of Interest for 3D Image Coding.
Abstract
For some 3D applications, one may want to focus on a specific depth zone representing a region of interest in the scene. In this context, we introduce a new functionality called źautofocusź for 3D image coding, exploiting the depth map as an additional semantic information provided by the 3D sequence. The method is based on a joint źDepth of Interestź (DoI) extraction and coding scheme. First, the DoI extraction scheme consists of a precise extraction of objects located within a DoI zone, given by the viewer or deduced from an analysis process. Then, the DoI coding scheme provides a higher quality for the objects in the DoI at the expense of other depth zones. The local quality enhancement supports both higher SNR and finer resolution. The proposed scheme embeds the Locally Adaptive Resolution (LAR) codec, initially designed for 2D images. The proposed DoI scheme is developed without modifying the global coder framework, and the DoI mask is not transmitted, but it is deduced at the decoder. Results showed that our proposed joint DoI extraction and coding scheme provide a high correlation between texture objects and depth. This consistency avoids the distortion along objects contours in depth maps and those of texture images and synthesized views.
Year
DOI
Venue
2017
10.1155/2017/9689715
J. Electrical and Computer Engineering
Field
DocType
Volume
Computer vision,Autofocus,Computer science,Coding (social sciences),Quality enhancement,Artificial intelligence,Region of interest,Depth map,Distortion,Codec,3d image
Journal
2017
ISSN
Citations 
PageRank 
2090-0147
0
0.34
References 
Authors
14
5
Name
Order
Citations
PageRank
Khouloud Samrouth173.18
Olivier Déforges217641.52
Yi Liu3103.96
M Khalil46721.26
Wassim E. L. Falou5112.19