Neural network based on template matching and its application in real-time target tracking

A novel neural network based on template matching is proposed for target recognition and tracking. Pixels in template and tracking window are arranged to form into loops, which are set to the threshold and the input of the neural network. The region where the sum of pixels in every loop is near the one in the template is chosen as the recognition result. Because the pixels are arranged into loops, the algorithm is of translation and rotation invariance. Furthermore, the calculated amount of the algorithm is somewhat less than that of MAD (minimum absolute difference). The algorithm can be applied to the real-time tracing system. The experimental results prove that the algorithm can satisfy the real-time need of the tracing system.