Electronics Projects:Target tracking

Implementation of 2D Target tracking using Kalman filter:

One of the fundamental problems in vision is that of tracking target through sequences of images. Target tracking is the problem of estimating the positions and other relevant information of moving target in image sequences. 

The Kalman filter is a set of mathematical equations that provides an efficient computational (recursive) means to estimate the state of a process, in a way that minimizes the mean of the squared error. The filter is very powerful in several aspects: it supports estimations of past, present, and even future states, and it can do so even when the precise nature of the modeled system is unknown.

The Kalman filter is the best filter among the subset of all linear filters and the best filter among the set of all filters when the noise processes are Gaussian type. The Kalman filter is essentially a set of mathematical equations that implement a predictor-corrector type estimator that is optimal in the sense that it minimizes the estimated error covariance- when some presumed conditions are met.

This project designs the Kalman filter algorithm to track the target and shows the resulting improvement in tracking as compared to other existing methods. It gives high-performance which can be used for real-time applications.