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. © 2011 Springer-Verlag.
CITATION STYLE
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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7102 LNAI, pp. 105–115). https://doi.org/10.1007/978-3-642-25489-5_11
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