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
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