Paper Info
Title
An Empirical Model of Multiview Video Coding Efficiency for Wireless Multimedia Sensor Networks
Abstract
We develop an empirical model of the Multiview Video Coding (MVC) performance that can be used to identify and separate situations when MVC is beneficial from cases when its use is detrimental in wireless multimedia sensor networks (WMSN). The model predicts the compression performance of MVC as a function of the correlation between cameras with overlapping fields of view. We define the common sensed area (CSA) between different views, and emphasize that it depends not only on geometrical relationships among the relative positions of different cameras, but also on various object-related phenomena, e.g., occlusions and motion, and on low-level phenomena such as variations in illumination. With these premises, we first experimentally characterize the relationship between MVC compression gain (with respect to single view video coding) and the CSA between views. Our experiments are based on the H.264 MVC standard, and on a low-complexity estimator of the CSA that can be computed with low inter-node signaling overhead. Then, we propose a compact empirical model of the efficiency of MVC as a function of the CSA between views, and we validate the model with different multiview video sequences. Finally, we show how the model can be applied to typical scenarios in WMSN, i.e., to clustered or multi-hop topologies, and we show a few promising results of its application in the definition of cross-layer clustering and data aggregation procedures.
Year
DOI
Venue
2013
10.1109/TMM.2013.2271475
IEEE Transactions on Multimedia
Keywords
Field
DocType
data communication,lighting,multimedia communication,telecommunication signalling,video coding,wireless sensor networks,CSA,H.264 MVC standard,MVC compression,MVC performance,WMSN,common sensed area,compact empirical model,compression performance,cross-layer clustering,data aggregation procedures,empirical model,geometrical relationships,illumination,inter-node signaling overhead,low-complexity estimator,low-level phenomena,multihop topologies,multiview video coding efhiciency,multiview video sequences,object-related phenomena,occlusions,wireless multimedia sensor networks,MVC efficiency model,Multiview video coding,video sensor networks
Computer vision,Computer science,Multiview Video Coding,Coding (social sciences),Network topology,Correlation,Artificial intelligence,Cluster analysis,Wireless sensor network,Data aggregator,Estimator
Journal
Volume
Issue
ISSN
15
8
1520-9210
Citations 
PageRank 
References 
12
0.60
11
Authors
3
Name
Order
Citations
PageRank
Stefania Colonnese113726.43
Francesca Cuomo267454.36
Tommaso Melodia34398290.59