Methods for vehicle detection and vehicle presence analysis for traffic applications

Oliver Sidla; Yuriy Lipetski

doi:10.1117/12.2036553

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

Oliver Sidla, Yuriy Lipetski

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.

Citation Download Citation

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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