Pedestrian tracking using single camera with new extended Kalman filter
Hadi Sadoghi Yazdi, Seyyed Ebrahim Hosseini · International Journal of Intelligent Computing and Cybernetics · 2008
Purpose The purpose of this paper is to present research in the area of the signal processing and application into pedestrian tracking in the video scene. Design/methodology/approach The paper describes the design of a new extended Kalman filter (EKF) in the high‐dimensional space (HDS) and studies of mean square error and variance analysis of error. A design algorithm is implemented in MATLAB software and tested. The data set includes many hours of captured films. Findings This paper includes a new derivation of the EKF and its implementation into the video scene. Practical implications The proposed algorithm can be used to track each video application. Originality/value The Kalman filter in the HDS is presented for the first time. Also, the application of the proposed method is applied in pedestrian tracking and counting.