NDLI: Jellyfish detection based on K-FOE residual map and ring segmentation

Content Provider	IEEE Xplore Digital Library
Author	Xiufen Wang Huiyuan Wang Song Wang
Copyright Year	2011
Description	Author affiliation: School of Information Science and Engineering, Shandong University, Jinan, 250100, China (Xiufen Wang; Huiyuan Wang; Song Wang)
Abstract	Target detection from underwater videos is a hot and difficult area in computer vision, especially when the camera has ego-motion. A jellyfish detection system is proposed for processing video streams captured by moving cameras mounted on remotely operated vehicles (ROVs). The background motion vector convergence point, or focus of expansion (FOE) is first found by solving equations with optical flows and then modified by Kalman filter prediction (K-FOE). Object templates are initialized by binarizing the K-FOE residual map. Subsequently, a ring segmentation subsystem is used to update the primitive object mask according to the distance between the object mask center and the K-FOE. All objects are extracted after their updated masks are obtained. Experimental results on real video data show that the proposed system can not only reduce fault detection but also extract small size jellyfish objects well.
Starting Page	762
Ending Page	766
File Size	294909
Page Count	5
File Format	PDF
ISBN	9781612843063
e-ISBN	9781612843070
DOI	10.1109/ICCT.2011.6157979
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer vision Optical imaging Optical filters Image motion analysis Adaptive optics Cameras Videos Jellyfish detection Foreground detection Kalman filter Focus of Expansion
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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