Open Access

Subgraphs Matching-Based Side Information Generation for Distributed Multiview Video Coding

  • Hongkai Xiong1, 2Email author,
  • Hui Lv1,
  • Yongsheng Zhang1,
  • Li Song1,
  • Zhihai He3 and
  • Tsuhan Chen2
EURASIP Journal on Advances in Signal Processing20102009:386795

Received: 23 April 2009

Accepted: 9 December 2009

Published: 22 March 2010


We adopt constrained relaxation for distributed multiview video coding (DMVC). The novel framework integrates the graph-based segmentation and matching to generate interview correlated side information without knowing the camera parameters, inspired by subgraph semantics and sparse decomposition of high-dimensional scale invariant feature data. The sparse data as a good hypothesis space aim for a best matching optimization of interview side information with compact syndromes, from inferred relaxed coset. The plausible filling-in from a priori feature constraints between neighboring views could reinforce a promising compensation to interview side-information generation for joint multiview decoding. The graph-based representations of multiview images are adopted as constrained relaxation, which assists the interview correlation matching for subgraph semantics of the original Wyner-Ziv image by the graph-based image segmentation and the associated scale invariant feature detector MSER (maximally stable extremal regions) and descriptor SIFT (scale-invariant feature transform). In order to find a distinctive feature matching with a more stable approximation, linear (PCA-SIFT) and nonlinear projections (Locally linear embedding) are adopted to reduce the dimension SIFT descriptors, and TPS (thin plate spline) warping model is to catch a more accurate interview motion model. The experimental results validate the high-estimation precision and the rate-distortion improvements.


Side InformationThin Plate SplineScale Invariant FeatureDescriptor SiftSparse Decomposition

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Authors’ Affiliations

Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, China
Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, USA
Department of Electrical and Computer Engineering, University of Missouri-Columbia, USA


© Hongkai Xiong et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.