Abstract
In this paper, we present a real-time vision-based multi-person tracking system working in crowded urban environments. Our approach combines stereo visual odometry estimation, HOG pedestrian detection, and multi-hypothesis tracking-by-detection to a robust tracking framework that runs on a single laptop with a CUDA-enabled graphics card. Through shifting the expensive computations to the GPU and making extensive use of scene geometry constraints we could build up a mobile system that runs with 10Hz. We experimentally demonstrate on several challenging sequences that our approach achieves competitive tracking performance.
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Mitzel, D., Floros, G., Sudowe, P., van der Zander, B., Leibe, B. (2011). Real Time Vision Based Multi-person Tracking for Mobile Robotics and Intelligent Vehicles. In: Jeschke, S., Liu, H., Schilberg, D. (eds) Intelligent Robotics and Applications. ICIRA 2011. Lecture Notes in Computer Science(), vol 7102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25489-5_11
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DOI: https://doi.org/10.1007/978-3-642-25489-5_11
Publisher Name: Springer, Berlin, Heidelberg
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