2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) Fast Human Detection Using a Cascade of Histograms of Oriented Gradients New York, NY June 17-June 22 ISBN: 0-7695-2597-0
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2006.119
We integrate the cascade-of-rejectors approach with the Histograms of Oriented Gradients (HoG) features to achieve a fast and accurate human detection system. The features used in our system are HoGs of variable-size blocks that capture salient features of humans automatically. Using AdaBoost for feature selection, we identify the appropriate set of blocks, from a large set of possible blocks. In our system, we use the integral image representation and a rejection cascade which significantly speed up the computation. For a 320 ? 280 image, the system can process 5 to 30 frames per second depending on the density in which we scan the image, while maintaining an accuracy level similar to existing methods.
Citation:
Qiang Zhu, Mei-Chen Yeh, Kwang-Ting Cheng, Shai Avidan, "Fast Human Detection Using a Cascade of Histograms of Oriented Gradients," cvpr, vol. 2, pp.1491-1498, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06), 2006 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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