Compressing a set of CHoG features

Vijay Chandrasekhar; Sam S. Tsai; Yuriy Reznik; Gabriel Takacs; David M. Chen; Bernd Girod

doi:10.1117/12.895431

24 September 2011 Compressing a set of CHoG features

Vijay Chandrasekhar, Sam S. Tsai, Yuriy Reznik, Gabriel Takacs, David M. Chen, Bernd Girod

Proceedings Volume 8135, Applications of Digital Image Processing XXXIV; 813517 (2011) https://doi.org/10.1117/12.895431
Event: SPIE Optical Engineering + Applications, 2011, San Diego, California, United States

Abstract

State-of-the-art image retrieval pipelines are based on "bag-of-words" matching. We note that the original order in which features are extracted from the image is discarded in the "bag-of-words" matching pipeline. As a result, a set of features extracted from a query image can be transmitted in any order. A set ofm unique features has m! orderings, and if the order of transmission can be discarded, one can reduce the query size by an additional log₂(m!) bits. In this work, we compare two schemes for discarding ordering: one based on Digital Search Trees, and another based on location histograms. We apply the two schemes to a set of low bitrate Compressed Histogram of Gradient (CHoG) features, and compare their performance. Both schemes achieve approximately log₂(m!) reduction in query size for a set of m features.

Citation Download Citation

Vijay Chandrasekhar, Sam S. Tsai, Yuriy Reznik, Gabriel Takacs, David M. Chen, and Bernd Girod "Compressing a set of CHoG features", Proc. SPIE 8135, Applications of Digital Image Processing XXXIV, 813517 (24 September 2011); https://doi.org/10.1117/12.895431

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