CHoG: Compressed Histogram of Gradients a Low Bit-Rate Feature Descriptor
Abstract
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 20× 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.
Cite
Text
Chandrasekhar et al. "CHoG: Compressed Histogram of Gradients a Low Bit-Rate Feature Descriptor." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009. doi:10.1109/CVPR.2009.5206733Markdown
[Chandrasekhar et al. "CHoG: Compressed Histogram of Gradients a Low Bit-Rate Feature Descriptor." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2009.](https://mlanthology.org/cvpr/2009/chandrasekhar2009cvpr-chog/) doi:10.1109/CVPR.2009.5206733BibTeX
@inproceedings{chandrasekhar2009cvpr-chog,
title = {{CHoG: Compressed Histogram of Gradients a Low Bit-Rate Feature Descriptor}},
author = {Chandrasekhar, Vijay and Takacs, Gabriel and Chen, David M. and Tsai, Sam S. and Grzeszczuk, Radek and Girod, Bernd},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2009},
pages = {2504-2511},
doi = {10.1109/CVPR.2009.5206733},
url = {https://mlanthology.org/cvpr/2009/chandrasekhar2009cvpr-chog/}
}