NDLI: Air-ground vehicle detection using local feature learning and saliency region detection

Content Provider	IEEE Xplore Digital Library
Author	Qinghan Xu Lizuo Jin Feiran Jie Shumin Fei
Copyright Year	2012
Description	Author affiliation: Science and Technology on Electro-optic Control Laboratory, Luoyang, 471009, China (Feiran Jie) \|\| School of Automation, Southeast University, Nanjing, 210096, China (Qinghan Xu; Lizuo Jin; Shumin Fei)
Abstract	Moving vehicle detection is very important for urban traffic surveillance and situational awareness on the battlefield. Algorithms with cascade structure like Adaboost are booming in the recent decade, and successful in realtime application. However, most of them use a sliding window protocol on multi-scale images which involves heavy computing. Therefore, they are only suitable for simple feature. In this paper, a biologically inspired method is proposed. We learn patch-based features for vehicle detection by unsupervised learning, and then employ a visual saliency step after feature extraction. Instead of sliding window, a candidate region is sent to classifier only if its features are “salient” on whole image. As the number of candidate regions decreases dramatically, it allow us to utilize complex feature to increase description ability. Experimental result indicates less computational expense and good performance.
Starting Page	4726
Ending Page	4731
File Size	721389
Page Count	6
File Format	PDF
ISBN	9781467313971
e-ISBN	9781467313988
DOI	10.1109/WCICA.2012.6359374
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Vehicles Visualization Unsupervised learning Vehicle detection Support vector machines Vectors saliency detection vehicle detection unsupervised learning
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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