, Volume 96, Issue 3, pp 384-399
Date: 15 May 2011

Compressed Histogram of Gradients: A Low-Bitrate Descriptor

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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.

This work was first presented as an oral presentation at Computer Vision and Pattern Recognition (CVPR), 2009. Since then, the authors have studied feature compression in more detail in Chandrasekhar et al. (2009a, 2010a, 2010b, 2010c). A default implementation of CHoG is available at http://www.stanford.edu/vijayc/.