Paper Info
Title
Angular Disparity Map: A Scalable Perceptual-Based Representation of Binocular Disparity
Abstract
This work addresses the data representation and the compression issues of angular disparity map following the way of HVS to perceive depth information. The continued fraction is utilized to represent the angular disparity map which enables the use of the state-of-the-art video codec (e.g. HEVC) to compress the data directly and maintains quality scalability properties. We observe that there is a non-monotonic phenomenon of the RD curves by applying HEVC compression to angular disparity map directly. This implies that the correlations among inter-layer (i.e., the neighboring integers in (2)) do not follow the traditional models of normal 2D video codecs. Of course, the detailed relationship between the sensitivities and the quantization errors of the newly proposed representation needs in depth further derivations. There are many interesting research issues may be introduced by the proposed data format (e.g., the sensitivities to quantization errors of θ and the rate-distortion optimization scheme for θ) which will, of course, be the research topics of our future work. We expect this work can be a bridge to connect the 3D perception and the 3D compression research fields.
Year
DOI
Venue
2013
10.1109/DCC.2013.85
DCC
Keywords
Field
DocType
image representation,binocular disparity scalable perceptual-based representation,quantization errors,binocular disparity,hvs,movie theater,normal 2d video codec models,different depth sensation,scalable perceptual-based representation,depth perception,angular difference,data compression,data format,rd curves,data representation,angular disparity map,angular disparity map representation,different depth perception,quality scalability properties,video coding,off-the-shelf low cost depth,pixel disparity,depth information,constant depth perception,nonmonotonic phenomenon,angular disparity,3d compression research fields,continued fraction,3d perception,hevc compression,video codecs,sensitivity,motion pictures
Integer,Computer vision,External Data Representation,Binocular disparity,Computer science,Theoretical computer science,Artificial intelligence,Quantization (signal processing),Data compression,Codec,Video compression picture types,Scalability
Conference
ISSN
ISBN
Citations 
1068-0314
978-1-4673-6037-1
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Yu-Hsun Lin117014.53
Ja-ling Wu21569168.11