4 March 2015 Close to real-time robust pedestrian detection and tracking
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Abstract
Fully automated video based pedestrian detection and tracking is a challenging task with many practical and important applications. We present our work aimed to allow robust and simultaneously close to real-time tracking of pedestrians. The presented approach is stable to occlusions, lighting conditions and is generalized to be applied on arbitrary video data. The core tracking approach is built upon tracking-by-detections principle. We describe our cascaded HOG detector with successive CNN verification in detail. For the tracking and re-identification task, we did an extensive analysis of appearance based features as well as their combinations. The tracker was tested on many hours of video data for different scenarios; the results are presented and discussed.
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Y. Lipetski, Y. Lipetski, G. Loibner, G. Loibner, O. Sidla, O. Sidla, } "Close to real-time robust pedestrian detection and tracking", Proc. SPIE 9407, Video Surveillance and Transportation Imaging Applications 2015, 94070C (4 March 2015); doi: 10.1117/12.2076136; https://doi.org/10.1117/12.2076136
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