Can We Detect Pedestrians using Low-resolution LIDAR? - Integration of Multi-frame Point-clouds

Yoshiki Tatebe, Daisuke Deguchi, Yasutomo Kawanishi, Ichiro Ide, Hiroshi Murase, Utsushi Sakai

2017

Abstract

In recent years, demand for pedestrian detection using inexpensive low-resolution LIDAR (LIght Detection And Ranging) is increasing, as it can be used to prevent traffic accidents involving pedestrians. However, it is difficult to detect pedestrians from a low-resolution (sparse) point-cloud obtained by a low-resolution LIDAR. In this paper, we propose multi-frame features calculated by integrating point-clouds over multiple frames for increasing the point-cloud resolution, and extracting their temporal changes. By combining these features, the accuracy of the pedestrian detection from low-resolution point-clouds can be improved. We conducted experiments using LIDAR data obtained in actual traffic environments. Experimental results showed that the proposed method could detect pedestrians accurately from low-resolution LIDAR data.

Paper Citation

in Harvard Style

Tatebe Y., Deguchi D., Kawanishi Y., Ide I., Murase H. and Sakai U. (2017). Can We Detect Pedestrians using Low-resolution LIDAR? - Integration of Multi-frame Point-clouds . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-226-4, pages 157-164. DOI: 10.5220/0006100901570164

in Bibtex Style

@conference{visapp17,
author={Yoshiki Tatebe and Daisuke Deguchi and Yasutomo Kawanishi and Ichiro Ide and Hiroshi Murase and Utsushi Sakai},
title={Can We Detect Pedestrians using Low-resolution LIDAR? - Integration of Multi-frame Point-clouds},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={157-164},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006100901570164},
isbn={978-989-758-226-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017)
TI - Can We Detect Pedestrians using Low-resolution LIDAR? - Integration of Multi-frame Point-clouds
SN - 978-989-758-226-4
AU - Tatebe Y.
AU - Deguchi D.
AU - Kawanishi Y.
AU - Ide I.
AU - Murase H.
AU - Sakai U.
PY - 2017
SP - 157
EP - 164
DO - 10.5220/0006100901570164