Binary descriptors have recently emerged as low-complexity alternatives to state-of-the-art descriptors such as SIFT. The descriptor is represented by means of a binary string, in which each bit is the result of the pairwise comparison of smoothed pixel values properly selected in a patch around each keypoint. Previous works have focused on the construction of the descriptor neglecting the opportunity of performing lossless compression. In this paper, we propose two contributions. First, design an entropy coding scheme that seeks the internal ordering of the descriptor that minimizes the number of bits necessary to represent it. Second, we compare different selection strategies that can be adopted to identify which pairwise comparisons to use when building the descriptor. Unlike previous works, we evaluate the discriminative power of descriptors as a function of rate, in order to investigate the trade-offs in a bandwidth constrained scenario.

Rate-accuracy optimization of binary descriptors

REDONDI, ALESSANDRO ENRICO CESARE;BAROFFIO, LUCA;CESANA, MATTEO;TAGLIASACCHI, MARCO
2013

Abstract

Binary descriptors have recently emerged as low-complexity alternatives to state-of-the-art descriptors such as SIFT. The descriptor is represented by means of a binary string, in which each bit is the result of the pairwise comparison of smoothed pixel values properly selected in a patch around each keypoint. Previous works have focused on the construction of the descriptor neglecting the opportunity of performing lossless compression. In this paper, we propose two contributions. First, design an entropy coding scheme that seeks the internal ordering of the descriptor that minimizes the number of bits necessary to represent it. Second, we compare different selection strategies that can be adopted to identify which pairwise comparisons to use when building the descriptor. Unlike previous works, we evaluate the discriminative power of descriptors as a function of rate, in order to investigate the trade-offs in a bandwidth constrained scenario.
2013 20th IEEE International Conference on Image Processing (ICIP)
9781479923410
Visual features; coding.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/760643
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