Target tracking using predicted Camshift

Camshift used color histogram as a characteristic, and used mean shift as the search algorithm. The direction of grads ascension was used to reduce the characteristic match time, so that the object orientation could be faster. Camshift could accurately follow the moving target under the simple backg...

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Published in2008 7th World Congress on Intelligent Control and Automation pp. 8501 - 8505
Main Authors Bo Yang, Hongjun Zhou, Xue Wang
Format Conference Proceeding
LanguageChinese
English
Published IEEE 01.06.2008
Subjects
Computer vision
Kalman filter
Kalman filters
Machine intelligence
Pattern analysis
predicted Camshift
Prediction algorithms
Real time systems
Target tracking
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ISBN1424421136
9781424421138
DOI10.1109/WCICA.2008.4594263

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Abstract Camshift used color histogram as a characteristic, and used mean shift as the search algorithm. The direction of grads ascension was used to reduce the characteristic match time, so that the object orientation could be faster. Camshift could accurately follow the moving target under the simple background, but at a complicated one it was very difficult for Camshift to accurately track a target. Predicted Camshift was used to track the real-time moving target in this paper. It takes the centroid of the Camshift as the observation signal, and adopts the Kalman filter to predict and correct the targetpsilas centroid. With this algorithm, it can accurately track the real-time moving target even under the interferential background.
AbstractList Camshift used color histogram as a characteristic, and used mean shift as the search algorithm. The direction of grads ascension was used to reduce the characteristic match time, so that the object orientation could be faster. Camshift could accurately follow the moving target under the simple background, but at a complicated one it was very difficult for Camshift to accurately track a target. Predicted Camshift was used to track the real-time moving target in this paper. It takes the centroid of the Camshift as the observation signal, and adopts the Kalman filter to predict and correct the targetpsilas centroid. With this algorithm, it can accurately track the real-time moving target even under the interferential background.
Author Bo Yang
Hongjun Zhou
Xue Wang
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  surname: Hongjun Zhou
  fullname: Hongjun Zhou
  organization: Sch. of Electron. Inf. Eng., Chongqing Univ. of Sci. & Technol., Chongqing
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  surname: Xue Wang
  fullname: Xue Wang
  organization: Sch. of Electron. Inf. Eng., Chongqing Univ. of Sci. & Technol., Chongqing
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Snippet Camshift used color histogram as a characteristic, and used mean shift as the search algorithm. The direction of grads ascension was used to reduce the...
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StartPage 8501
SubjectTerms Computer vision
Kalman filter
Kalman filters
Machine intelligence
Pattern analysis
predicted Camshift
Prediction algorithms
Real time systems
Target tracking
Title Target tracking using predicted Camshift
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