International Journal of Computer Vision

, Volume 96, Issue 3, pp 384-399

First online:

Compressed Histogram of Gradients: A Low-Bitrate Descriptor

  • Vijay ChandrasekharAffiliated withStanford University Email author 
  • , Gabriel TakacsAffiliated withStanford University
  • , David M. ChenAffiliated withStanford University
  • , Sam S. TsaiAffiliated withStanford University
  • , Yuriy ReznikAffiliated withStanford University
  • , Radek GrzeszczukAffiliated withStanford University
  • , Bernd GirodAffiliated withStanford University

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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.


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