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19 July 2013 A new algorithm for pedestrian detection
Ke-yang Cheng, Jun-xian Bao
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Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 88783C (2013) https://doi.org/10.1117/12.2031762
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China
Abstract
This article puts forward a novel framework for pedestrian detection tasks, which proposing a model with both sparse reconstruction and class discrimination components, jointly optimized during dictionary learning. We present an efficient pedestrian detection system using mixing sparse features of HOG, FOG and CSS to combine into a Kernel classifier. Results presented on our data set show competitive accuracy and robust performance of our system outperforms current state-of-the-art work.
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Ke-yang Cheng and Jun-xian Bao "A new algorithm for pedestrian detection", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88783C (19 July 2013); https://doi.org/10.1117/12.2031762
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KEYWORDS
Associative arrays
RGB color model
Detection and tracking algorithms
Binary data
Computer programming
Fiber optic gyroscopes
Astronomical engineering
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