Pedestrian Tracking based on 3D Head Point Detection

Zhongchuan Zhang, Fernand Cohen

Abstract

In this paper, we introduce a 3D pedestrian tracking method based on 3D head point detection in indoor environment, such as train stations, airports, shopping malls and hotel lobbies where the ground can be non-flat. We also show that our approach is effective and efficient in capturing close-up facial images using pan-tilt-zoom (PTZ) cameras. We use two horizontally displaced overhead cameras to track pedestrians by estimating the accurate 3D position of their heads. The 3D head point is then tracked using common assumptions on motion direction and velocity. Our method is able to track pedestrians in 3D space no matter if the pedestrian is walking on a planar or a non-planar surface. Moreover, we make no assumption about the pedestrians’ heights, nor do we have to generate the full disparity map of the scene. The tracking system architecture allows for a real time capturing of high quality facial images by guiding PTZ cameras. The approach is tested using a publicly available visual surveillance simulation test bed.

References

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Paper Citation


in Harvard Style

Zhang Z. and Cohen F. (2013). Pedestrian Tracking based on 3D Head Point Detection . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 382-385. DOI: 10.5220/0004232203820385


in Bibtex Style

@conference{visapp13,
author={Zhongchuan Zhang and Fernand Cohen},
title={Pedestrian Tracking based on 3D Head Point Detection},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={382-385},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004232203820385},
isbn={978-989-8565-48-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Pedestrian Tracking based on 3D Head Point Detection
SN - 978-989-8565-48-8
AU - Zhang Z.
AU - Cohen F.
PY - 2013
SP - 382
EP - 385
DO - 10.5220/0004232203820385