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Received: 2008-03-18

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Crosschecked: 2008-12-26

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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.6 P.786~793

http://doi.org/10.1631/jzus.A0820198


Robust water hazard detection for autonomous off-road navigation


Author(s):  Tuo-zhong YAO, Zhi-yu XIANG, Ji-lin LIU

Affiliation(s):  Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   thomasyao@zju.edu.cn, xiangzy@zju.edu.cn

Key Words:  Water hazard detection, Active learning, Adaboost, Mean-shift


Tuo-zhong YAO, Zhi-yu XIANG, Ji-lin LIU. Robust water hazard detection for autonomous off-road navigation[J]. Journal of Zhejiang University Science A, 2009, 10(6): 786~793.

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author="Tuo-zhong YAO, Zhi-yu XIANG, Ji-lin LIU",
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T1 - Robust water hazard detection for autonomous off-road navigation
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DOI - 10.1631/jzus.A0820198


Abstract: 
Existing water hazard detection methods usually fail when the features of water surfaces are greatly changed by the surroundings, e.g., by a change in illumination. This paper proposes a novel algorithm to robustly detect different kinds of water hazards for autonomous navigation. Our algorithm combines traditional machine learning and image segmentation and uses only digital cameras, which are usually affordable, as the visual sensors. active learning is used for automatically dealing with problems caused by the selection, labeling and classification of large numbers of training sets. mean-shift based image segmentation is used to refine the final classification. Our experimental results show that our new algorithm can accurately detect not only ‘common’ water hazards, which usually have the features of both high brightness and low texture, but also ‘special’ water hazards that may have lots of ripples or low brightness.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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[2] Dima, C., 2004. Classifier Fusion for Outdoor Obstacle Detection. IEEE Int. Conf. on Robotics and Automation, 1:665-671.

[3] Dima, C., 2006. Active Learning for Outdoor Perception. PhD Thesis, the Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA.

[4] Dima, C., Hebert, M., Stentz, A., 2004. Enabling Learning from Large Datasets: Applying Active Learning to Mobile Robotics. Proc. Int. Conf. on Robotics and Automation, 1:108-114.

[5] Forsyth, D., Ponce, J., 2002. Computer Vision: A Modern Approach. Professional Technical Reference, Prentice Hall.

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[7] Hong, T., Chang, T., Rasmussen, C., Shneier, M., 2002. Feature Detection and Tracking for Mobile Robots Using a Combination of Radar and Color Images. IEEE Proc. on Robotics and Automation, p.4340-4345.

[8] Matthies, L., Bellutta, P., McHenry, M., 2003. Detecting Water Hazards for Autonomous Off-road Navigation. SPIE, 5083:231-242.

[9] Nguyen, N., Milanfar, P., Golub, G., 2001. Efficient generalized cross-validation with application parametric image restoration and resolution enhancement. IEEE Trans. Image Processing, 10(9):1299-1308.

[10] Nigam, K., 2001. Using Unlabeled Data to Improve Text Classification. PhD Thesis, Carnegie Mellon University, Pittsburgh, PA, USA.

[11] Rankin, A., Matthies, L., Huertas, A., 2004. Daytime Water Detection by Fusing Multiple Cues for Autonomous Off-road Navigation. Proc. 24th Army Science Conf., p.177-184.

[12] Sarwal, A., Nett, J., Simon, D., 2004. Detection of Small Water-bodies. Technical Report, PercepTek Robotics, USA.

[13] Scholz, M., Vigario, R., 2002. Nonlinear PCA: A New Hierarchical Approach. Proc. European Symp. on Artificial Neural Networks, p.439-444.

[14] Wald, I., Havran, V., 2006. On Building Fast kd-trees for Ray Tracing, and on Doing That in O(NlogN). IEEE Symp. on Interactive Ray Tracing, p.61-70.

[15] Yao, T.Z., Xiang, Z.Y., Liu, J.L., Xu, D., 2007. Multi-feature Fusion Based Outdoor Water Hazards Detection. Proc. IEEE Conf. on Mechatronics and Automation, p.652-656.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Teoh Chee Way@UTAR<teohcw@utar.edu.my>

2010-11-02 23:10:10

Dear Yao,

I am very interested in your work "Robust water hazard detection for autonomous off-road navigation". However, I could not access it under Springerlink as the journal is not under my subscription.

I seek your assistance to provide a copy of your work. I would like to see in details of your work.

Your help will be very much appreciated.

Thank you.

Best Regards,
Teoh Chee Way

Please provide your name, email address and a comment





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