loading
Documents

Research.Publish.Connect.

Paper

Authors: Taiki Yamamoto 1 ; Fumito Shinmura 2 ; Daisuke Deguchi 3 ; Yasutomo Kawanishi 1 ; Ichiro Ide 1 and Hiroshi Murase 1

Affiliations: 1 Graduate School of Informatics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya-shi, Aichi, Japan ; 2 Institutes of Innovation for Future Society, Nagoya University, Furo-cho, Chikusa-ku, Nagoya-shi, Aichi, Japan ; 3 Information Strategy Office, Nagoya University, Furo-cho, Chikusa-ku, Nagoya-shi, Aichi, Japan

ISBN: 978-989-758-354-4

Keyword(s): Active-scan LIDAR, Stochastic Sampling, Pedestrian Detection.

Abstract: In recent years, LIDAR is playing an important role as a sensor for understanding environments of a vehicle’s surroundings. Active-scan LIDAR is being actively developed as a LIDAR that can control the laser irradiation direction arbitrary and rapidly. In comparison with conventional uniform-scan LIDAR (e.g. Velodyne HDL-64e), Active-scan LIDAR enables us to densely scan even distant pedestrians. In addition, if appropriately controlled, this sensor has a potential to reduce unnecessary laser irradiations towards non-target objects. Although there are some preliminary studies on pedestrian scanning strategy for Active-scan LIDARs, in the best of our knowledge, an efficient method has not been realized yet. Therefore, this paper proposes a novel pedestrian scanning method based on orientation aware pedestrian likelihood estimation using the orientation-wise pedestrian’s shape models with local distribution of measured points. To evaluate the effectiveness of the proposed method, we con ducted experiments by simulating Active-scan LIDAR using point-clouds from the KITTI dataset. Experimental results showed that the proposed method outperforms the conventional methods. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.171.146.16

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Yamamoto, Taiki; Shinmura, F.; Deguchi, D.; Kawanishi, Y.; Ide, I. and Murase, H. (2019). Pedestrian Intensive Scanning for Active-scan LIDAR.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-354-4, pages 313-320. DOI: 10.5220/0007359903130320

@conference{visapp19,
author={Yamamoto, Taiki and Fumito Shinmura. and Daisuke Deguchi. and Yasutomo Kawanishi. and Ichiro Ide. and Hiroshi Murase.},
title={Pedestrian Intensive Scanning for Active-scan LIDAR},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2019},
pages={313-320},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007359903130320},
isbn={978-989-758-354-4},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Pedestrian Intensive Scanning for Active-scan LIDAR
SN - 978-989-758-354-4
AU - Yamamoto, Taiki
AU - Shinmura, F.
AU - Deguchi, D.
AU - Kawanishi, Y.
AU - Ide, I.
AU - Murase, H.
PY - 2019
SP - 313
EP - 320
DO - 10.5220/0007359903130320

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.