期刊文献+

Improved Video Moving Target Tracking Based on Camshift 被引量:3

Improved Video Moving Target Tracking Based on Camshift
下载PDF
导出
摘要 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. 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.
作者 Liang Li Yi Luo Liang Li;Yi Luo(The College of Automation and Electronic Information, Sichuan University of Science & Engineering, Zigong, China)
出处 《American Journal of Computational Mathematics》 2016年第4期357-364,共8页 美国计算数学期刊(英文)
关键词 CAMSHIFT Target Tracking Gaussian Mixture Model Kalman Prediction Object Shelter Camshift Target Tracking Gaussian Mixture Model Kalman Prediction Object Shelter
  • 相关文献

同被引文献32

引证文献3

二级引证文献16

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部