A Hybrid Method Using Temporal and Spatial Information for 3D Lidar Data Segmentation

Mehmet Ali Çağrı Tuncer, Dirk Schulz

Abstract

This paper proposes a novel hybrid segmentation method for 3D Light Detection and Ranging (Lidar) data. The presented approach gains robustness against the under-segmentation issue, i.e., assigning several objects to one segment, by jointly using spatial and temporal information to discriminate nearby objects in the data. When an autonomous vehicle has a complex dynamic environment, such as pedestrians walking close to their nearby objects, determining if a segment consists of one or multiple objects can be difficult with spatial features alone. The temporal cues allow us to resolve such ambiguities. In order to get temporal information, a motion field of the environment is estimated for subsequent 3D Lidar scans based on an occupancy grid representation. Then we propose a hybrid approach using the mean-shift method and the distance dependent Chinese Restaurant Process (ddCRP). After the segmentation blobs are spatially extracted from the scene, the mean-shift seeks the number of possible objects in the state space of each blob. If the mean-shift algorithm determines an under-segmented blob, the ddCRP performs the final partition in this blob. Otherwise, the queried blob remains the same and it is assigned as a segment. The computational time of the hybrid method is below the scanning period of the Lidar sensor. This enables the system to run in real time.

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Paper Citation


in Harvard Style

Tuncer M. and Schulz D. (2017). A Hybrid Method Using Temporal and Spatial Information for 3D Lidar Data Segmentation . In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-264-6, pages 162-171. DOI: 10.5220/0006471101620171


in Bibtex Style

@conference{icinco17,
author={Mehmet Ali Çağrı Tuncer and Dirk Schulz},
title={A Hybrid Method Using Temporal and Spatial Information for 3D Lidar Data Segmentation},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2017},
pages={162-171},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006471101620171},
isbn={978-989-758-264-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - A Hybrid Method Using Temporal and Spatial Information for 3D Lidar Data Segmentation
SN - 978-989-758-264-6
AU - Tuncer M.
AU - Schulz D.
PY - 2017
SP - 162
EP - 171
DO - 10.5220/0006471101620171