Disparity estimation for multi-scale multi-sensor fusion
SUN Guoliang 1PEI Shanshan 2LONG Qian 3ZHENG Sifa 4YANG Rui5
作者信息
- 1. Suzhou Automotive Research Institute,Tsinghua University,Suzhou 215000,China
- 2. Beijing Smarter Eye Technology Co.,Ltd.,Beijing 100023,China
- 3. College of Artifical Intelligence,Tianjin University of Science and Technology,Tianjin 300457,China
- 4. State Key Laboratory of Automotive Safety and Energy,Tsinghua University,Beijing 100084,China
- 5. Department of Precision Instrument,Tsinghua University,Beijing 100084,China
- 折叠
Abstract
The perception module of advanced driver assis-tance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor com-posed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experi-ments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map esti-mation.
Key words
stereo vision/light deterction and ranging(LiDAR)/multi-sensor fusion/multi-scale fusion/disparity map引用本文复制引用
基金项目
国家重点研发计划(2018AAA0103103)
出版年
2024
NETL
NSTL
维普
万方数据