A sensor fusion system with thermal infrared camera and LiDAR for autonomous vehicles and deep learning based object detection

Citations

WEB OF SCIENCE

95
Citations

SCOPUS

130

초록

Vision, Radar, and LiDAR sensors are widely used for autonomous vehicle perception technology. Especially object detection and classification are primarily dependent on vision sensors. However, under poor lighting conditions, dazzling sunlight, or bad weather an object might be difficult to be identified with general vision sensors. In this paper, we propose a sensor fusion system that combines a thermal infrared camera and a LiDAR sensor that can reliably detect and identify objects even in environments with poor visibility, such as day or night. The proposed method obtains the external parameters of the two sensors by designing and manufacturing a 3D calibration target to externally calibrate the thermal infrared camera and the LiDAR sensor. To verify the performance, experiments were conducted in day and night environments. The proposed sensor system and fusion algorithm show that it can reliably detect and identify objects even in environments with poor visibility, such as day or night. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

키워드

Sensor fusion; LiDAR; Thermal infrared camera; Autonomous vehicles; Object detection; Convolution neural network
제목
A sensor fusion system with thermal infrared camera and LiDAR for autonomous vehicles and deep learning based object detection
저자
Choi, Ji Dong; Kim, Min Young
DOI
10.1016/j.icte.2021.12.016
발행일
2023-04
유형
Article
저널명
ICT Express
권
9
호
2
페이지
222 ~ 227