Pedestrian tracking using single camera with new extended Kalman filter

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.

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.

This paper includes a new derivation of the EKF and its implementation into the video scene.

The proposed algorithm can be used to track each video application.

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.