Methods for vehicle detection and vehicle presence analysis for traffic applications

Oliver Sidla; Yuriy Lipetski

doi:10.1117/12.2036553

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5 March 2014 Methods for vehicle detection and vehicle presence analysis for traffic applications

Oliver Sidla, Yuriy Lipetski

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Proceedings Volume 9026, Video Surveillance and Transportation Imaging Applications 2014; 90260R (2014) https://doi.org/10.1117/12.2036553
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

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.

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Oliver Sidla and Yuriy Lipetski "Methods for vehicle detection and vehicle presence analysis for traffic applications", Proc. SPIE 9026, Video Surveillance and Transportation Imaging Applications 2014, 90260R (5 March 2014); https://doi.org/10.1117/12.2036553

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