Result: Support Vector Machine based Fusion for Multi-view Distributed Video Coding
Title:
Support Vector Machine based Fusion for Multi-view Distributed Video Coding
Authors:
Contributors:
Laboratoire Traitement et Communication de l'Information (LTCI), Télécom ParisTech-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)
Source:
International Conference on Digital Signal Processing (DSP2011).
Publisher Information:
HAL CCSD, 2011.
Publication Year:
2011
Collection:
collection:INSTITUT-TELECOM
collection:CNRS
collection:ENST
collection:TELECOM-PARISTECH
collection:PARISTECH
collection:LTCI
collection:INSTITUTS-TELECOM
collection:INSTITUT-MINES-TELECOM
collection:CNRS
collection:ENST
collection:TELECOM-PARISTECH
collection:PARISTECH
collection:LTCI
collection:INSTITUTS-TELECOM
collection:INSTITUT-MINES-TELECOM
Subject Terms:
Subject Geographic:
Original Identifier:
HAL: hal-01436399
Document Type:
Conference
conferenceObject<br />Conference papers
Language:
English
Access URL:
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.hal.01436399v1
Database:
HAL
Further Information
In multi-view Distributed Video Coding, Side Information can be computed either from previously decoded frames in the same view, or from previously decoded frames in adjacent views. In this paper, we address the problem of effectively fusing these two predictions. For this purpose, we propose two Support Vector Machine based fusion algorithms. We also identify a number of features to be used in classification. Experimental results show the efficiency of the proposed approach and its robustness over test sequences with greatly varying characteristics.