Coding of Image Feature Descriptors for Distributed Rate-efficient Visual Correspondences

  • Authors:

  • Chuohao Yeo;Parvez Ahammad;Kannan Ramchandran

  • Affiliations:

  • Signal Processing Department, Institute for Infocomm Research, Singapore, Singapore 118936;Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, USA 20147;Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, USA 94720

  • Venue:
  • International Journal of Computer Vision
  • Year:
  • 2011

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Abstract

Establishing visual correspondences is a critical step in many computer vision tasks involving multiple views of a scene. In a dynamic environment and when cameras are mobile, visual correspondences need to be updated on a recurring basis. At the same time, the use of wireless links between camera motes imposes tight rate constraints. This combination of issues motivates us to consider the problem of establishing visual correspondences in a distributed fashion between cameras operating under rate constraints. We propose a solution based on constructing distance preserving hashes using binarized random projections. By exploiting the fact that descriptors of regions in correspondence are highly correlated, we propose a novel use of distributed source coding via linear codes on the binary hashes to more efficiently exchange feature descriptors for establishing correspondences across multiple camera views. A systematic approach is used to evaluate rate vs visual correspondences retrieval performance; under a stringent matching criterion, our proposed methods demonstrate superior performance to a baseline scheme employing transform coding of descriptors.