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Tang, Q., Dai, S.G. and Yang, J. (2013) Object Tracking Algorithm Based on Camshift Combining Background Subtraction with Three Frame Difference. In: Kim, Y.-H., Ed., Applied Mechanics and Materials, Trans Tech Publications Inc., Switzerland, 1116-1119.
https://doi.org/10.4028/www.scientific.net/amm.373-375.1116

has been cited by the following article:

• TITLE: Improved Video Moving Target Tracking Based on Camshift

  AUTHORS: Liang Li, Yi Luo

  KEYWORDS: Camshift, Target Tracking, Gaussian Mixture Model, Kalman Prediction, Object Shelter

  JOURNAL NAME: American Journal of Computational Mathematics, Vol.6 No.4, December 29, 2016

  ABSTRACT: Focusing on the failure under the condition of target blocking, the similarity between target color and background color for the Camshift algorithm, an improved algorithm based on Camshift algorithm is proposed. Gaussian mixture model is used to determine the tracking area fast and accurately because it is not sensitive to the external conditions such as light and shadow. Kalman predictor is used to predict the blocked target effectively. The video is processed in the MATLAB environment. The moving target can be tracked and its position can be predicted accurately with the proposed improved algorithm. The results verify the feasibility and effectiveness of the algorithm.