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Proceedings Paper

Methods for vehicle detection and vehicle presence analysis for traffic applications
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Paper Abstract

This paper presents our work towards robust vehicle detection in dynamic and static scenes from a brief historical perspective up to our current state-of-the-art. We cover several methods (PCA, basic HOG, texture analysis, 3D measurement) which have been developed for, tested, and used in real-world scenarios. The second part of this work presents a new HOG cascade training algorithm which is based on evolutionary optimization principles: HOG features for a low stage count cascade are learned using genetic feature selection methods. We show that with this approach it is possible to create a HOG cascade which has comparable performance to an AdaBoost trained cascade, but is much faster to evaluate.

Paper Details

Date Published: 5 March 2014
PDF: 12 pages
Proc. SPIE 9026, Video Surveillance and Transportation Imaging Applications 2014, 90260R (5 March 2014); doi: 10.1117/12.2036553
Show Author Affiliations
Oliver Sidla, SLR Engineering GmbH (Austria)
Yuriy Lipetski, SLR Engineering GmbH (Austria)


Published in SPIE Proceedings Vol. 9026:
Video Surveillance and Transportation Imaging Applications 2014
Robert P. Loce; Eli Saber; Ned Lecky, Editor(s)

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