Depth-based target segmentation for intelligent vehicles: fusion of radar and binocular stereo
Fang, Y.
Masaki, I.
Horn, B.
Artificial Intelligence Lab., MIT, Cambridge, MA ;
This paper appears in: Intelligent Transportation Systems, IEEE Transactions on
Publication Date: Sep 2002
Volume: 3,
Issue: 3
On page(s): 196- 202
ISSN: 1524-9050
INSPEC Accession Number: 7406585
Digital Object Identifier: 10.1109/TITS.2002.802926
Current Version Published: 2002-11-07
Abstract
Dynamic environment interpretation is of special interest for intelligent vehicle systems. It is expected to provide lane information, target depth, and the image positions of targets within given depth ranges. Typical segmentation algorithms cannot solve the problems satisfactorily, especially under the high-speed requirements of a real-time environment. Furthermore, the variation of image positions and sizes of targets creates difficulties for tracking. In this paper, we propose a sensor-fusion method that can make use of coarse target depth information to segment target locations in video images. Coarse depth ranges can be provided by radar systems or by a vision-based algorithm introduced in the paper. The new segmentation method offers more accuracy and robustness while decreasing the computational load.
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
