Novel Vehicle Bounding Box Tracking Using a Low-End 3D Laser Scanner

Jhonghyun An; Euntai Kim

doi:10.1109/TITS.2020.2994624

Novel Vehicle Bounding Box Tracking Using a Low-End 3D Laser Scanner

Jhonghyun An, Euntai Kim

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Vehicle bounding box tracking (VBBT) is a new problem that is becoming increasingly important in autonomous driving. It is defined as a problem in which not only the position but also the size of a target vehicle is estimated using a sensor. In this paper, novel VBBT using a low-end three-dimensional (3D) laser scanner is proposed. Compared to previous methods, the proposed VBBT has three distinctions: (1) the center of a rectangular vehicle is defined as its position, and the motion model that uses the center of the vehicle as the state is developed; (2) a new measurement model is proposed that models the measured size of the target vehicle as a sample from a uniform distribution; and (3) a Bayesian filter for the proposed motion and measurement model is developed and it is named as the Pareto Kalman filter (PKF). Finally, the proposed method is applied to six scenarios, and its validity is demonstrated through experimentation.

Original language	English
Article number	9098054
Pages (from-to)	3403-3419
Number of pages	17
Journal	IEEE Transactions on Intelligent Transportation Systems
Volume	22
Issue number	6
DOIs	https://doi.org/10.1109/TITS.2020.2994624
Publication status	Published - 2021 Jun

Bibliographical note

Funding Information:
Manuscript received October 16, 2019; revised March 10, 2020; accepted May 8, 2020. Date of publication May 21, 2020; date of current version June 2, 2021. This work was supported by the National Research Foundation of Korea (NRF) through the Basic Science Research Program funded by the Ministry of Education, Science, and Technology under Grant NRF-2019R1A2C1007153. The Associate Editor for this article was L. M. Bergasa. (Corresponding author: Euntai Kim.) The authors are with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea (e-mail: jhonghyen@yonsei.ac.kr; etkim@yonsei.ac.kr). Digital Object Identifier 10.1109/TITS.2020.2994624

Publisher Copyright:
© 2000-2011 IEEE.

All Science Journal Classification (ASJC) codes

Automotive Engineering
Mechanical Engineering
Computer Science Applications

Access to Document

10.1109/TITS.2020.2994624

Cite this

@article{940d99b47fae4343bc0156bca9cdea93,

title = "Novel Vehicle Bounding Box Tracking Using a Low-End 3D Laser Scanner",

abstract = "Vehicle bounding box tracking (VBBT) is a new problem that is becoming increasingly important in autonomous driving. It is defined as a problem in which not only the position but also the size of a target vehicle is estimated using a sensor. In this paper, novel VBBT using a low-end three-dimensional (3D) laser scanner is proposed. Compared to previous methods, the proposed VBBT has three distinctions: (1) the center of a rectangular vehicle is defined as its position, and the motion model that uses the center of the vehicle as the state is developed; (2) a new measurement model is proposed that models the measured size of the target vehicle as a sample from a uniform distribution; and (3) a Bayesian filter for the proposed motion and measurement model is developed and it is named as the Pareto Kalman filter (PKF). Finally, the proposed method is applied to six scenarios, and its validity is demonstrated through experimentation. ",

author = "Jhonghyun An and Euntai Kim",

note = "Funding Information: Manuscript received October 16, 2019; revised March 10, 2020; accepted May 8, 2020. Date of publication May 21, 2020; date of current version June 2, 2021. This work was supported by the National Research Foundation of Korea (NRF) through the Basic Science Research Program funded by the Ministry of Education, Science, and Technology under Grant NRF-2019R1A2C1007153. The Associate Editor for this article was L. M. Bergasa. (Corresponding author: Euntai Kim.) The authors are with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea (e-mail: jhonghyen@yonsei.ac.kr; etkim@yonsei.ac.kr). Digital Object Identifier 10.1109/TITS.2020.2994624 Publisher Copyright: {\textcopyright} 2000-2011 IEEE.",

year = "2021",

month = jun,

doi = "10.1109/TITS.2020.2994624",

language = "English",

volume = "22",

pages = "3403--3419",

journal = "IEEE Transactions on Intelligent Transportation Systems",

issn = "1524-9050",

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

number = "6",

}

TY - JOUR

T1 - Novel Vehicle Bounding Box Tracking Using a Low-End 3D Laser Scanner

AU - An, Jhonghyun

AU - Kim, Euntai

N1 - Funding Information: Manuscript received October 16, 2019; revised March 10, 2020; accepted May 8, 2020. Date of publication May 21, 2020; date of current version June 2, 2021. This work was supported by the National Research Foundation of Korea (NRF) through the Basic Science Research Program funded by the Ministry of Education, Science, and Technology under Grant NRF-2019R1A2C1007153. The Associate Editor for this article was L. M. Bergasa. (Corresponding author: Euntai Kim.) The authors are with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea (e-mail: jhonghyen@yonsei.ac.kr; etkim@yonsei.ac.kr). Digital Object Identifier 10.1109/TITS.2020.2994624 Publisher Copyright: © 2000-2011 IEEE.

PY - 2021/6

Y1 - 2021/6

N2 - Vehicle bounding box tracking (VBBT) is a new problem that is becoming increasingly important in autonomous driving. It is defined as a problem in which not only the position but also the size of a target vehicle is estimated using a sensor. In this paper, novel VBBT using a low-end three-dimensional (3D) laser scanner is proposed. Compared to previous methods, the proposed VBBT has three distinctions: (1) the center of a rectangular vehicle is defined as its position, and the motion model that uses the center of the vehicle as the state is developed; (2) a new measurement model is proposed that models the measured size of the target vehicle as a sample from a uniform distribution; and (3) a Bayesian filter for the proposed motion and measurement model is developed and it is named as the Pareto Kalman filter (PKF). Finally, the proposed method is applied to six scenarios, and its validity is demonstrated through experimentation.

AB - Vehicle bounding box tracking (VBBT) is a new problem that is becoming increasingly important in autonomous driving. It is defined as a problem in which not only the position but also the size of a target vehicle is estimated using a sensor. In this paper, novel VBBT using a low-end three-dimensional (3D) laser scanner is proposed. Compared to previous methods, the proposed VBBT has three distinctions: (1) the center of a rectangular vehicle is defined as its position, and the motion model that uses the center of the vehicle as the state is developed; (2) a new measurement model is proposed that models the measured size of the target vehicle as a sample from a uniform distribution; and (3) a Bayesian filter for the proposed motion and measurement model is developed and it is named as the Pareto Kalman filter (PKF). Finally, the proposed method is applied to six scenarios, and its validity is demonstrated through experimentation.

UR - http://www.scopus.com/inward/record.url?scp=85107428909&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85107428909&partnerID=8YFLogxK

U2 - 10.1109/TITS.2020.2994624

DO - 10.1109/TITS.2020.2994624

M3 - Article

AN - SCOPUS:85107428909

VL - 22

SP - 3403

EP - 3419

JO - IEEE Transactions on Intelligent Transportation Systems

JF - IEEE Transactions on Intelligent Transportation Systems

SN - 1524-9050

IS - 6

M1 - 9098054

ER -

Novel Vehicle Bounding Box Tracking Using a Low-End 3D Laser Scanner

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this