Depth-based target segmentation for intelligent vehicles: fusion of radar and binocular stereo
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 unde...
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| Veröffentlicht in: | IEEE transactions on intelligent transportation systems 2002-09, Vol.3 (3), p.196-202 |
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| creator | Fang, Y. Masaki, I. Horn, B. |
| description | 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. |
| doi_str_mv | 10.1109/TITS.2002.802926 |
| format | Article |
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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. 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| ispartof | IEEE transactions on intelligent transportation systems, 2002-09, Vol.3 (3), p.196-202 |
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| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms Dynamical systems Dynamics Image segmentation Intelligent sensors Intelligent vehicles Machine vision Motion detection Object detection Radar Radar detection Radar imaging Robustness Segmentation Spatial resolution |
| title | Depth-based target segmentation for intelligent vehicles: fusion of radar and binocular stereo |
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