Title :
DepthFinder, a real-time depth detection system for aided driving
Author :
Murphey, Y.L. ; Chen, J. ; Crossman, J. ; Zhang, J. ; Richardson, P. ; Sieh, L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Michigan Univ., Dearborn, MI, USA
Abstract :
Many military applications require the distance information from a moving vehicle to targets from video image sequences. For indirect driving, lack of perception of depth in view hinders steering and navigation. In this paper we present a real-time depth detection system DepthFinder, a system that finds the distances of objects through a monocular vision model. DepthFinder can be used with a camera mounted either at the front of side of a moving vehicle. A real-time matching algorithm is introduced to improve the matching performance by several orders of magnitude. The experiment results and the performance analysis are presented
Keywords :
computer vision; computerised navigation; image matching; image sequences; motion estimation; real-time systems; road vehicles; DepthFinder; computer vision; depth detection system; image matching; image sequences; monocular vision model; navigation; real-time system; road vehicles; steering; Application software; Cameras; Equations; Image sequences; Lenses; Military computing; Navigation; Real time systems; Stereo vision; Vehicles;
Conference_Titel :
Intelligent Vehicles Symposium, 2000. IV 2000. Proceedings of the IEEE
Conference_Location :
Dearborn, MI
Print_ISBN :
0-7803-6363-9
DOI :
10.1109/IVS.2000.898329
