Target tracking based on the cognitive associative network

Abstract

To extend the application of the cognitive associative network and improve the performance of the target tracking method, a novel tracking method based on the new network is proposed, i.e. the cognitive associative network is transformed and used to perform the target tracking. The local hue histograms are used to model the target, and the circle matching criterion is used to locate the target, which can restrain the disturbance from the adjacent regions in the background. It can also adjust adaptively the size of the tracking target according to the local matching results. Therefore, the tracking method based on the cognitive associative network has good invariability to the scale, the rotation, and the partial occlusion. Simulation results show that the tracking method can perform the target tracking in the disturbance environment or in the scene of the complex motion. The tracking method can locate the target more accurately than the common tracking methods such as the Camshift method or the compressive tracking method.