Target Tracking Based on Improved Camshift and Kalman Filter

Li Ying Ban; Yue Hua Han; Yan Hai Wu

doi:10.4028/www.scientific.net/AMR.989-994.3587

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Relevance Feedback Based on Particle Swarm Optimize Weight-Vector for Image Retrieval
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Design of Optical Fiber Transmission System Based on Absolute Polar Duty Cycle Division Multiplexing (APDCDM)
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 989-994Target Tracking Based on Improved Camshift and...

Target Tracking Based on Improved Camshift and Kalman Filter

Abstract:

A tracking algorithm based on improved Camshift and Kalman filter is proposed in this paper to deal with the problems in traditional Camshift algorithm, such as tracking failure under color interference or occlusion. Firstly, the proposed algorithm improves the single color target model and presents a novel target model, which fuses color and motion cues, to enhance the robustness and accuracy of target tracking. And in order to increase the tracking efficiency, the algorithm combines Kalman filter with the improved Camshift algorithm by using Kalman filter to predict the position of the tracking target under color noises and occlusion. The experiment results demonstrate that the proposed algorithm can track the target object accurately and has better robustness.

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Periodical:

Advanced Materials Research (Volumes 989-994)

Pages:

3587-3590

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.989-994.3587

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Online since:

July 2014

Authors:

Li Ying Ban*, Yue Hua Han, Yan Hai Wu

Keywords:

Camshift, Data Fusion, Kalman Filter, Kim Algorithm, Target Tracking

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