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.