International Journal of Computer Vision

, Volume 96, Issue 3, pp 384–399

Compressed Histogram of Gradients: A Low-Bitrate Descriptor

  • Vijay Chandrasekhar
  • Gabriel Takacs
  • David M. Chen
  • Sam S. Tsai
  • Yuriy Reznik
  • Radek Grzeszczuk
  • Bernd Girod
Article

Abstract

Establishing visual correspondences is an essential component of many computer vision problems, which is often done with local feature-descriptors. Transmission and storage of these descriptors are of critical importance in the context of mobile visual search applications. We propose a framework for computing low bit-rate feature descriptors with a 20× reduction in bit rate compared to state-of-the-art descriptors. The framework offers low complexity and has significant speed-up in the matching stage. We show how to efficiently compute distances between descriptors in the compressed domain eliminating the need for decoding. We perform a comprehensive performance comparison with SIFT, SURF, BRIEF, MPEG-7 image signatures and other low bit-rate descriptors and show that our proposed CHoG descriptor outperforms existing schemes significantly over a wide range of bitrates. We implement the descriptor in a mobile image retrieval system and for a database of 1 million CD, DVD and book covers, we achieve 96% retrieval accuracy using only 4 KB of data per query image.

Keywords

CHoG Feature descriptor Mobile visual search Content-based image retrieval Histogram-of-gradients Low bitrate 

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Vijay Chandrasekhar
    • 1
  • Gabriel Takacs
    • 1
  • David M. Chen
    • 1
  • Sam S. Tsai
    • 1
  • Yuriy Reznik
    • 1
  • Radek Grzeszczuk
    • 1
  • Bernd Girod
    • 1
  1. 1.Stanford UniversityStanfordUSA

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