Towards Multi-Object Detection and Tracking in Urban Scenario under Uncertainties

Achim Kampker, Mohsen Sefati, Arya S. Abdul Rachman, Kai Kreisköther, Pascual Campoy

Abstract

Urban-oriented autonomous vehicles require a reliable perception technology to tackle the high amount of uncertainties. The recently introduced compact 3D LIDAR sensor offers a surround spatial information that can be exploited to enhance the vehicle perception. We present a real-time integrated framework of multi-target object detection and tracking using 3D LIDAR geared toward urban use. Our approach combines sensor occlusion-aware detection method with computationally efficient heuristics rule-based filtering and adaptive probabilistic tracking to handle uncertainties arising from sensing limitation of 3D LIDAR and complexity of the target object movement. The evaluation results using real-world pre-recorded 3D LIDAR data and comparison with state-of-the-art works shows that our framework is capable of achieving promising tracking performance in the urban situation.

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Paper Citation


in Harvard Style

Kampker A., Sefati M., Abdul Rachman A., Kreisköther K. and Campoy P. (2018). Towards Multi-Object Detection and Tracking in Urban Scenario under Uncertainties.In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-293-6, pages 156-167. DOI: 10.5220/0006706101560167


in Bibtex Style

@conference{vehits18,
author={Achim Kampker and Mohsen Sefati and Arya S. Abdul Rachman and Kai Kreisköther and Pascual Campoy},
title={Towards Multi-Object Detection and Tracking in Urban Scenario under Uncertainties},
booktitle={Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2018},
pages={156-167},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006706101560167},
isbn={978-989-758-293-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Towards Multi-Object Detection and Tracking in Urban Scenario under Uncertainties
SN - 978-989-758-293-6
AU - Kampker A.
AU - Sefati M.
AU - Abdul Rachman A.
AU - Kreisköther K.
AU - Campoy P.
PY - 2018
SP - 156
EP - 167
DO - 10.5220/0006706101560167