Visual multi-target tracking by using modified Kohonen Neural Networks

A visual target tracking identification by employing using a ldquowinner-takes-allrdquo artificial neural network is proposed in this paper. In this approach a modified Kohonen neural network is the mechanism used both to determine the position as to represent the target trajectory given a sequence of images. Some of the advantages employing this technique is that the initial condition are supplied randomly and that the performance of the algorithm is independent of the initial condition as well as of the number of them. Besides, this algorithm converge for the center of mass of the target. This methodology is useful in remote and local systems when information is given by images be it related to aerospace applications, robotics, radar systems, or industrial applications. The proposed algorithm is here used in the identification of airplane trajectory by using digital images.