Tracking of video objects based on Kalman filter

Abstract EN

Object tracking is an important task within the field of computer vision.

Where, it is the process of segmenting an object of interest from a video scene and keeping track of its motion, orientation occlusion to extract useful information.

This paper is intended to the improve the measurement accuracy of the closing moving object by using the median filter for denoising and Kalman filter for tracking.

At the denoising stage, 70-80% of the noise is reduced by using a median filter.

The median filter has been used instead of the Wiener filter because the noise which is assumed is salt and pepper, and it is less complexity than the Wiener filter.

While in the tracking stage, the KF has been used as estimated filter.

However, the measurements have been improved by 11.27%.

The simulation has been done by using Matlab 2014, while the proposal is applied to the real video.