A Sensor Fusion System with Thermal Infrared Camera and LiDAR for Autonomous Vehicles: Its Calibration and. Application

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WEB OF SCIENCE

15
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SCOPUS

23

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, risiziling sunlight, or bad weathers an object might be difficult to be identified with general vision sensors. In this paper, we propose a sensor fission system with a thermal infrared camera and LiDAR sensor that can reliably detect and identify objects even in environments where visibility is poor, such as in severe glare and fog or smoke. The proposed method obtains intrinsic parameters by calibrating the thermal infrared camera and LiDAR sensor. Extrinsic calibration algorithm between two sensors is made to obtain the extrinsic parameters (rotation and translation matrix) using 3D calibration targets. This system and proposed algorithm show that it can reliably detect and identify objects even in hard visibility environments, such as in severe glare due to direct sunlight or headlights or in low visibility environments, such as in severe fog or smoke.

키워드

Calibration; Autonomous Vehicles; Sensor fusion; LiDAR; Thermal Infrared Camera
제목
A Sensor Fusion System with Thermal Infrared Camera and LiDAR for Autonomous Vehicles: Its Calibration and. Application
저자
Choi, Ji Dong; Kim, Min Young
DOI
10.1109/ICUFN49451.2021.9528609
발행일
2021
유형
Proceedings Paper
저널명
International Conference on Ubiquitous and Future Networks, ICUFN
페이지
361 ~ 365