CHoG: Compressed histogram of gradients A low bit-rate feature descriptor
CVPR(2009)
摘要
Establishing visual correspondences is an essential component of
many computer vision problems, and is often done with robust, local
feature-descriptors. Transmission and storage of these descriptors
are of critical importance in the context of mobile distributed camera
networks and large indexing problems. We propose a framework for
computing low bit-rate feature descriptors with a 20times reduction
in bit rate. The framework is low complexity and has significant
speed-up in the matching stage. We represent gradient histograms
as tree structures which can be efficiently compressed. We show how
to efficiently compute distances between descriptors in their compressed
representation eliminating the need for decoding. We perform a comprehensive
performance comparison with SIFT, SURF, and other low bit-rate descriptors
and show that our proposed CHoG descriptor outperforms existing schemes.
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关键词
computer vision,feature extraction,gradient methods,compressed histogram,computer vision,gradient histogram,low bit-rate feature descriptor,tree structure
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