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Authors: Mehmet Ali Çağrı Tuncer and Dirk Schulz

Affiliation: Fraunhofer FKIE, Germany

ISBN: 978-989-758-264-6

Keyword(s): Object Segmentation, Distance Dependent Chinese Restaurant Process, Mean Shift, 3D Lidar Data.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Mobile Robots and Autonomous Systems ; Perception and Awareness ; Robotics and Automation

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 poss ible 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. (More)

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Paper citation in several formats:
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

@conference{icinco17,
author={Mehmet Ali \c{C}ağrı 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},
}

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

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