DocumentCode :
519568
Title :
Automatic Camshift tracking algorithm based on fuzzy inference background difference combining with twice searching
Author :
Gang, Xiao ; Yong, Chen ; Jiu-Jun, Chen ; Fei, Gao
Author_Institution :
Coll. of Comput. Sci. & Technol., Zhejiang Univ. of Technol., Hangzhou, China
Volume :
1
fYear :
2010
fDate :
17-18 April 2010
Firstpage :
1
Lastpage :
4
Abstract :
In order to overcome the shortcoming that traditional Camshift needs artificial orientation during tracking, this paper proposes a new approach of Camshift tracking algorithm based on fuzzy inference background difference. In this paper, the object contour extracted by background difference rather than artificial selection, is used as initial search window so as to realize automatic Camshift tracking. Meanwhile, to avoid object divergence and object losing when the object moves too quickly, twice Camshift searching is combined with background difference to enlarge the search window automatically to ensure consistent targeting. Furthermore, this paper also introduces contour marking and multiple Camshift trackers to implement successful multi-object tracking. Methods mentioned above prove themselves efficient and automatic in tracking one or more moving fishes during the experiments.
Keywords :
feature extraction; fuzzy reasoning; object detection; automatic camshift tracking algorithm; continuously adaptive meanshift algorithm; contour marking; fuzzy inference background difference; initial search window; multiobject tracking; object contour extraction; object divergence; twice searching; Cities and towns; Computer science; Ecosystems; Educational institutions; Fuzzy neural networks; Inference algorithms; Iterative algorithms; Marine animals; Probability distribution; Target tracking; Camshift; background difference; contour marking; object tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Health Networking, Digital Ecosystems and Technologies (EDT), 2010 International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-5514-0
Type :
conf
DOI :
10.1109/EDT.2010.5496634
Filename :
5496634
Link To Document :
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