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Proceedings Paper

A conditional random field model for 3D reconstruction in image sequences
Author(s): Dazhi Zhang; Junbin Gong; Yongtao Wang
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Paper Abstract

An airborne vehicle must avoid obstacles like towers, fences, tree branches, mountains and building across the flight path. So the ability to detect and locate obstacles using on-board sensors is an essential step in the autonomous navigation of aircraft low-altitude flight. In this paper, a novel passive range method using conditional random field (CRF) is presented to map the 3D scene in front of a moving aircraft with image sequences obtained from a forward-looking imaging sensor. Finally, An dynamic graph cuts method was presented for the CRF model to recursively update thedepth map. Experimental data demonstrates the effectiveness of our approach.

Paper Details

Date Published: 30 October 2009
PDF: 6 pages
Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74961E (30 October 2009); doi: 10.1117/12.832739
Show Author Affiliations
Dazhi Zhang, Huazhong Univ. of Science and Technology (China)
Junbin Gong, Huazhong Univ. of Science and Technology (China)
Yongtao Wang, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 7496:
MIPPR 2009: Pattern Recognition and Computer Vision
Mingyue Ding; Bir Bhanu; Friedrich M. Wahl; Jonathan Roberts, Editor(s)

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