Video Target Tracking Based on Adaptive Kalman Filter

Video tracking technology is a hot topic in computer vision research. Video tracking technology is widely used, such as robot vision, intelligent traffic management, medical diagnosis and intelligent monitoring. Therefore, it is of theoretical significance and practical value to study video target tracking technology. In this paper, the background subtraction method and adaptive Kalman filter are combined to realize real time video target tracking. The experimental results show that the proposed method can improve the tracking accuracy.

[1]  Mohammad Reza Taban,et al.  A novel intelligent adaptive Kalman Filter for estimating the Submarine's velocity: With experimental evaluation , 2018 .

[2]  K. V. Sriharsha,et al.  Dynamic scene analysis using Kalman filter and mean shift tracking algorithms , 2015, 2015 6th International Conference on Computing, Communication and Networking Technologies (ICCCNT).

[3]  Fuad A. Ghaleb,et al.  Improved vehicle positioning algorithm using enhanced innovation-based adaptive Kalman filter , 2017, Pervasive and Mobile Computing.

[4]  Vivek Maik,et al.  Object tracking using block motion estimation with adaptive Kalman estimates , 2017, 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT).

[5]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[6]  Ying Tan,et al.  SINS/CNS integrated navigation solution using adaptive unscented Kalman filtering , 2011, Int. J. Comput. Appl. Technol..

[7]  Zhenyu Huang,et al.  Adaptive adjustment of noise covariance in Kalman filter for dynamic state estimation , 2017, 2017 IEEE Power & Energy Society General Meeting.