The Kalman filter has been used successfully in different prediction applications or state determination of a system. One of the more important fields in computer vision is the object tracking. Different movement conditions and occlusions can hinder the vision tracking of an object. In this report we present the use of the Kalman filter as a predictor in vision tracking. We consider the capacit...

In this paper a new method of frequency tracking based on modified adaptive notch filter is proposed to solve the problem of dynamic frequency tracking of low capacity power system, the ANF equations is discretizated, the influence of the ANF parameters on frequency tracking is analyzed, the band-pass pre-filter and the low-pass post-filter are applied. With applying iterative updates synchrono...

In this research paper, we introduce Lane Tracking by Using navigation,positioning and tracking filter i.e dealing to make the hybrid of two filter.This two filters are “Kalman filter and Particle filter”. Presented approach gives us idea about perfect and efficient and clear view tracking. Model is designed to make a tracking near real time. This idea further introduces the lane detection whic...

Object tracking through multiple cameras is a popular research topic in security and surveillance systems especially when human objects are the target. However, occlusion is one of the challenging problems for the tracking process. This paper proposes a multiple-camera-based cooperative tracking method to overcome the occlusion problem.  The paper presents a new model for combining convolutiona...

It is known that the Kalman filter estimation performance heavily depends on the statistical parameters to both the dynamic and observation models, especially the covariance matrix Q. This paper presents a fast genetic algorithm (GA) to adapt extended Kalman filter (EKF) for real time tracking. In the proposed method, the covariance matrix Q can be real-time adjusted by GA to meet some specific...