Efficient Rectangle Fitting of Sparse Laser Data for Robust On-Road Obiect Detection

Shuai Yang; Zhaohong Xiang; Jin Wu; Xiao Wang; Hongbin Sun; Jinming Xin; Nanning Zheng

doi:10.1109/IVS.2018.8500716

Efficient Rectangle Fitting of Sparse Laser Data for Robust On-Road Obiect Detection

Shuai Yang
, Zhaohong Xiang
, Jin Wu
, Xiao Wang
, Hongbin Sun
, Jinming Xin
, Nanning Zheng

College of Artificial Intelligence and Robotics

Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

On-road object detection is one of the most important tasks for the autonomous driving of intelligent vehicle. Nevertheless, the previous methods based on 2D LIDAR sensor only focus on the detection of vehicles, and show severe limitations on the detection of other objects. Accordingly, this paper proposes an on-road object detection method, which employs rectangle fitting and concavity determination to improve the robustness of ob- ject detection. The proposed approaches are extensively evaluated by using the sparse laser data collected by 2D LIDAR from real traffic environment. Experimental results demonstrate that the proposed rectangle fitting outperforms the previous approaches in terms of both detection accuracy and computational efficiency.

Original language	English
Title of host publication	2018 IEEE Intelligent Vehicles Symposium, IV 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	846-853
Number of pages	8
ISBN (Electronic)	9781538644522
DOIs	https://doi.org/10.1109/IVS.2018.8500716
State	Published - 18 Oct 2018
Event	2018 IEEE Intelligent Vehicles Symposium, IV 2018 - Changshu, Suzhou, China Duration: 26 Sep 2018 → 30 Sep 2018

Publication series

Name	IEEE Intelligent Vehicles Symposium, Proceedings
Volume	2018-June

Conference

Conference	2018 IEEE Intelligent Vehicles Symposium, IV 2018
Country/Territory	China
City	Changshu, Suzhou
Period	26/09/18 → 30/09/18

Access to Document

10.1109/IVS.2018.8500716

Cite this

Yang, S., Xiang, Z., Wu, J., Wang, X., Sun, H., Xin, J., & Zheng, N. (2018). Efficient Rectangle Fitting of Sparse Laser Data for Robust On-Road Obiect Detection. In 2018 IEEE Intelligent Vehicles Symposium, IV 2018 (pp. 846-853). Article 8500716 (IEEE Intelligent Vehicles Symposium, Proceedings; Vol. 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IVS.2018.8500716

@inproceedings{91e5997f23e649d09f6bcb35e99deeca,

title = "Efficient Rectangle Fitting of Sparse Laser Data for Robust On-Road Obiect Detection",

abstract = "On-road object detection is one of the most important tasks for the autonomous driving of intelligent vehicle. Nevertheless, the previous methods based on 2D LIDAR sensor only focus on the detection of vehicles, and show severe limitations on the detection of other objects. Accordingly, this paper proposes an on-road object detection method, which employs rectangle fitting and concavity determination to improve the robustness of ob- ject detection. The proposed approaches are extensively evaluated by using the sparse laser data collected by 2D LIDAR from real traffic environment. Experimental results demonstrate that the proposed rectangle fitting outperforms the previous approaches in terms of both detection accuracy and computational efficiency.",

author = "Shuai Yang and Zhaohong Xiang and Jin Wu and Xiao Wang and Hongbin Sun and Jinming Xin and Nanning Zheng",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Intelligent Vehicles Symposium, IV 2018 ; Conference date: 26-09-2018 Through 30-09-2018",

year = "2018",

month = oct,

day = "18",

doi = "10.1109/IVS.2018.8500716",

language = "英语",

series = "IEEE Intelligent Vehicles Symposium, Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "846--853",

booktitle = "2018 IEEE Intelligent Vehicles Symposium, IV 2018",

}

Yang, S, Xiang, Z, Wu, J, Wang, X, Sun, H , Xin, J & Zheng, N 2018, Efficient Rectangle Fitting of Sparse Laser Data for Robust On-Road Obiect Detection. in 2018 IEEE Intelligent Vehicles Symposium, IV 2018., 8500716, IEEE Intelligent Vehicles Symposium, Proceedings, vol. 2018-June, Institute of Electrical and Electronics Engineers Inc., pp. 846-853, 2018 IEEE Intelligent Vehicles Symposium, IV 2018, Changshu, Suzhou, China, 26/09/18. https://doi.org/10.1109/IVS.2018.8500716

Efficient Rectangle Fitting of Sparse Laser Data for Robust On-Road Obiect Detection. / Yang, Shuai; Xiang, Zhaohong; Wu, Jin et al.
2018 IEEE Intelligent Vehicles Symposium, IV 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 846-853 8500716 (IEEE Intelligent Vehicles Symposium, Proceedings; Vol. 2018-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Efficient Rectangle Fitting of Sparse Laser Data for Robust On-Road Obiect Detection

AU - Yang, Shuai

AU - Xiang, Zhaohong

AU - Wu, Jin

AU - Wang, Xiao

AU - Sun, Hongbin

AU - Xin, Jinming

AU - Zheng, Nanning

PY - 2018/10/18

Y1 - 2018/10/18

N2 - On-road object detection is one of the most important tasks for the autonomous driving of intelligent vehicle. Nevertheless, the previous methods based on 2D LIDAR sensor only focus on the detection of vehicles, and show severe limitations on the detection of other objects. Accordingly, this paper proposes an on-road object detection method, which employs rectangle fitting and concavity determination to improve the robustness of ob- ject detection. The proposed approaches are extensively evaluated by using the sparse laser data collected by 2D LIDAR from real traffic environment. Experimental results demonstrate that the proposed rectangle fitting outperforms the previous approaches in terms of both detection accuracy and computational efficiency.

AB - On-road object detection is one of the most important tasks for the autonomous driving of intelligent vehicle. Nevertheless, the previous methods based on 2D LIDAR sensor only focus on the detection of vehicles, and show severe limitations on the detection of other objects. Accordingly, this paper proposes an on-road object detection method, which employs rectangle fitting and concavity determination to improve the robustness of ob- ject detection. The proposed approaches are extensively evaluated by using the sparse laser data collected by 2D LIDAR from real traffic environment. Experimental results demonstrate that the proposed rectangle fitting outperforms the previous approaches in terms of both detection accuracy and computational efficiency.

UR - https://www.scopus.com/pages/publications/85056798655

U2 - 10.1109/IVS.2018.8500716

DO - 10.1109/IVS.2018.8500716

M3 - 会议稿件

AN - SCOPUS:85056798655

T3 - IEEE Intelligent Vehicles Symposium, Proceedings

SP - 846

EP - 853

BT - 2018 IEEE Intelligent Vehicles Symposium, IV 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE Intelligent Vehicles Symposium, IV 2018

Y2 - 26 September 2018 through 30 September 2018

ER -

Efficient Rectangle Fitting of Sparse Laser Data for Robust On-Road Obiect Detection

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this