caa a22 4500 605540462 CHVBK 20210128100911.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s00371-014-0918-5 doi (NATIONALLICENCE)springer-10.1007/s00371-014-0918-5 Real-time obstacle detection with motion features using monocular vision [Elektronische Daten] [Baozhi Jia, Rui Liu, Ming Zhu] Real-time obstacle detection by monocular vision is a challenging problem in autonomous navigation of vehicles and driver-assistance systems. In this paper, we introduce an approach of real-time obstacle detection which can effectively tell apart obstacles from shadows and road surface markings. We propose the followings: (1) a two consecutive frames (TCF) model to find the differences between obstacles and the ground plane by motion features; (2) a filter to increase probabilities of obstacle regions; (3) an updating process to reduce false positives and update the algorithm when the vehicle moves on. We perform experiments on two datasets and our autonomous vehicle. The results show that our method is effective in various conditions and meets the real-time requirement. Springer-Verlag Berlin Heidelberg, 2014 Autonomous navigation nationallicence Driver-assistance systems nationallicence Real-time obstacle detect nationallicence Feature points nationallicence Monocular vision nationallicence Jia Baozhi University of Science and Technology of China, 230026, Hefei, Anhui, People's Republic of China aut Liu Rui University of Science and Technology of China, 230026, Hefei, Anhui, People's Republic of China aut Zhu Ming University of Science and Technology of China, 230026, Hefei, Anhui, People's Republic of China aut The Visual Computer Springer Berlin Heidelberg 31/3(2015-03-01), 281-293 0178-2789 31:3<281 2015 31 371 https://doi.org/10.1007/s00371-014-0918-5 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00371-014-0918-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Jia Baozhi University of Science and Technology of China, 230026, Hefei, Anhui, People's Republic of China aut NATIONALLICENCE 700 1- Liu Rui University of Science and Technology of China, 230026, Hefei, Anhui, People's Republic of China aut NATIONALLICENCE 700 1- Zhu Ming University of Science and Technology of China, 230026, Hefei, Anhui, People's Republic of China aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/3(2015-03-01), 281-293 0178-2789 31:3<281 2015 31 371