DocumentCode :
3351033
Title :
Automatic video-based analysis of animal behaviors
Author :
Fan, Jialue ; Jiang, Nan ; Wu, Ying
Author_Institution :
Dept. of EECS, Northwestern Univ., Evanston, IL, USA
fYear :
2010
fDate :
26-29 Sept. 2010
Firstpage :
1513
Lastpage :
1516
Abstract :
Vision-based animal behavior analysis is a critical and interesting problem for both biologists and computer vision scientists. In this paper, an automatic system for detecting behaviors of fruit flies is presented. Firstly, we propose an ellipse model to fit the contours of fruit flies, which efficiently detects fruit flies in a single frame. Then we associate the detection results together to form the trajectories. An AdaBoost classifier is used to analyze special behaviors of flies. The experiments show that our system can robustly track fruit flies and detect the fly behaviors with high recall rate in real time. This system has been adopted to aid biologists for research purposes.
Keywords :
computer vision; video signal processing; AdaBoost classifier; automatic system; automatic video-based analysis; biologists; computer vision scientists; ellipse model; fruit flies; vision-based animal behavior analysis; Biological information theory; Cameras; Feature extraction; Pixel; Trajectory; Video sequences; action detection; video analysis; vision application;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1522-4880
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2010.5652495
Filename :
5652495
Link To Document :
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