Object Tracking Using Improved Meanshift Algorithm Combined with Kalman Filter on Independent Visual Robotic Fish

Hai Hua Shi; Wei Xiang

doi:10.4028/www.scientific.net/AMM.333-335.1030

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 333-335Object Tracking Using Improved Meanshift Algorithm...

Object Tracking Using Improved Meanshift Algorithm Combined with Kalman Filter on Independent Visual Robotic Fish

Abstract:

This Paper Investigates an Improved Meanshift Algorithm Combined with Kalman Filter Aiming at Failure of a Target Tracking in Complex Environment for the Independent Visual Robotic Fish. First,we Need to Establish Kalman Filter Model of Moving Target. then,the Prediction and Renewal Process of Kalman Filter are Applied into the Meanshift Tracking Algorithm. Experimental Results Show that Improved Algorithm can Effectively Improve the Performance of Single Target Tracking in Complex Environment, and Realize Continuous Tracking of a Target. also, it can Obtain more Reliable Tracking Effect, and can be Used for more Complicated Scenes.

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Periodical:

Applied Mechanics and Materials (Volumes 333-335)

Pages:

1030-1033

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.333-335.1030

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Cite this paper

Online since:

July 2013

Authors:

Hai Hua Shi*, Wei Xiang

Keywords:

Complex Environment, Kalman Filter (KF), Meanshift Algorithm, Object Tracking, Robotic Fish

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* - Corresponding Author

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