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Multimodal Object Detection and Ranging Based on Camera and Lidar Sensor Fusion for Autonomous Driving
- Khan, Danish;
- Baek, Minjin;
- Kim, Min Young;
- Han, Dong Seog
WEB OF SCIENCE
10SCOPUS
15초록
A robust perception system is critical in autonomous driving. It is responsible for object detection, classification, and ranging under challenging circumstances. Camera and lidar sensors provide complementary information, and by combining these two modalities, we can increase the robustness and accuracy of the overall perception system. This paper presents the implementation of sensor fusion based perception using camera images and lidar point clouds for object detection and ranging in a real-time driving environment. The experiment results obtained with our test vehicle demonstrate that the perception of vehicle surroundings can be more effectively achieved by means of camera-lidar sensor fusion compared with using a single type of sensor.
키워드
- 제목
- Multimodal Object Detection and Ranging Based on Camera and Lidar Sensor Fusion for Autonomous Driving
- 저자
- Khan, Danish; Baek, Minjin; Kim, Min Young; Han, Dong Seog
- 발행일
- 2022
- 유형
- Proceedings Paper
- 저널명
- 2022 27TH ASIA PACIFIC CONFERENCE ON COMMUNICATIONS (APCC 2022): CREATING INNOVATIVE COMMUNICATION TECHNOLOGIES FOR POST-PANDEMIC ERA
- 페이지
- 342 ~ 343
- 언어
- ENG
- 출판사
- IEEE
- 발행국가
- 미국
- 분량
- 2 페이지