Two-stage obstacle detection based on stereo vision in unstructured environment

Zhang, Y; Xu, X; Lu, H; Dai, Y

Two-stage obstacle detection based on stereo vision in unstructured environment

Zhang, Y Xu, X Lu, H

Dai, Y

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2014 6th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2014, 2014, 1 pp. 168 - 172
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Zhang, Y	en_US
dc.contributor.author	Xu, X	en_US
dc.contributor.author	Lu, H https://orcid.org/0000-0001-5655-0237	en_US
dc.contributor.author	Dai, Y	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Proceedings - 2014 6th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2014, 2014, 1 pp. 168 - 172	en_US
dc.identifier.isbn	9781479949557	en_US
dc.identifier.uri	http://hdl.handle.net/10453/43437
dc.description.abstract	© 2014 IEEE. In an unstructured environment, there are many challenges for obstacle detection. This paper presents an improved method to detect obstacles based on stereo vision in unstructured environments based on salient obstacle extraction. This method can achieve same or higher level of accuracy of obstacle detection compared to the existing salient obstacle detection with significant reduction of computation time. This method consists of two stages. In the first stage, it extracts the salient obstacles which stand out from the background in the stereo images using a fast salient obstacle detection method. In the second stage, it refines the detection of small obstacles by computing the geometric relationships among 3D points using an improved space-variant resolution (SVR) with the continuity and the height constraints. The experiment results show that this improved method can reduce computation time and improve detection accuracy.	en_US
dc.relation.ispartof	Proceedings - 2014 6th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2014	en_US
dc.relation.isbasedon	10.1109/IHMSC.2014.49	en_US
dc.title	Two-stage obstacle detection based on stereo vision in unstructured environment	en_US
dc.type	Conference Proceeding
utslib.citation.volume	1	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	1	en_US

Abstract:

© 2014 IEEE. In an unstructured environment, there are many challenges for obstacle detection. This paper presents an improved method to detect obstacles based on stereo vision in unstructured environments based on salient obstacle extraction. This method can achieve same or higher level of accuracy of obstacle detection compared to the existing salient obstacle detection with significant reduction of computation time. This method consists of two stages. In the first stage, it extracts the salient obstacles which stand out from the background in the stereo images using a fast salient obstacle detection method. In the second stage, it refines the detection of small obstacles by computing the geometric relationships among 3D points using an improved space-variant resolution (SVR) with the continuity and the height constraints. The experiment results show that this improved method can reduce computation time and improve detection accuracy.

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http://hdl.handle.net/10453/43437