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Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)
Algorithm for Tracking of Fast Motion Objects with Adaptive Mean Shift
Haier International Training Center, Qingdao, China
July 30-August 01
ISBN: 0-7695-2909-7
ASCII Text
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Guo-liang Wang, De-qun Liang, Yan-chun Wang, Zhao-hua Hu, "Algorithm for Tracking of Fast Motion Objects with Adaptive Mean Shift," Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on, vol. 1, pp. 359-363, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007.
 
 
BibTex
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@article{ 10.1109/SNPD.2007.152,
author = {Guo-liang Wang and De-qun Liang and Yan-chun Wang and Zhao-hua Hu},
title = {Algorithm for Tracking of Fast Motion Objects with Adaptive Mean Shift},
journal ={Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on},
volume = {1},
year = {2007},
isbn = {0-7695-2909-7},
pages = {359-363},
doi = {http://doi.ieeecomputersociety.org/10.1109/SNPD.2007.152},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
TI - Algorithm for Tracking of Fast Motion Objects with Adaptive Mean Shift
SN - 0-7695-2909-7
SP359
EP363
A1 - Guo-liang Wang,
A1 - De-qun Liang,
A1 - Yan-chun Wang,
A1 - Zhao-hua Hu,
PY - 2007
KW - null
VL - 1
JA - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
ER -
 
Guo-liang Wang, Dalian Maritime University, China
De-qun Liang, Dalian Maritime University, China
Yan-chun Wang, Dalian Maritime University, China
Zhao-hua Hu, Dalian Maritime University, China; Nanjing University of Science & Technology, China
The Classic Kernel-Based Object Tracking algorithm uses fixed kernel-bandwidth, which limits the performance when the object scale exceeds the size of the tracking window and the object fast motion. Therefor, a real-time object tracking algorithm is proposed, This algorithm gets the target?s scale using automatic selection of kernel-bandwidth based on feature matching. Based on the analysis of similarity of object kernel-histogram by object center distance-weighting, gets the target?s location by mean-shift Algorithm. Experimental results show that the proposed algorithm can track successfully fast moving objects of changing in size.
Citation:
Guo-liang Wang, De-qun Liang, Yan-chun Wang, Zhao-hua Hu, "Algorithm for Tracking of Fast Motion Objects with Adaptive Mean Shift," snpd, vol. 1, pp.359-363, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007
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