標題: LiDAR/Camera Sensor Fusion Technology for Pedestrian Detection
作者: Wu, Tai-En
Tsai, Chia-Chi
Guo, Jiun-In
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
公開日期: 1-一月-2017
摘要: Nowadays, the machine learning for object detection is growing popular and widely adopted in many fields, such as surveillance, automotive, passenger flow analysis, etc. This paper focuses on the research of Lidar/camera sensor fusion technology for pedestrian detection to ensure extremely high detection accuracy. In order to reduce the false-positive rate and the object occlusion problem, which usually happened in camera-based pedestrian detection, we use 3D point cloud returning from Lidar depth sensor to do the further examination on the object's shape. The proposed Lidar/camera sensor fusion design complements the advantage and disadvantage of two sensors such that it is more stable in detection than others. The region proposal is given from both sensors, and candidate front two sensors are also going to the second classification for double checking. It maximums the detection rate and achieves average 99.16% detection accuracy for pedestrian detection.
URI: http://hdl.handle.net/11536/146971
ISSN: 2309-9402
期刊: 2017 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC 2017)
起始頁: 1675
結束頁: 1678
顯示於類別:會議論文