Human Tracking Using Wigner Distribution and Rule-Based System in RGB Video

Abstract

In recent times, human tracking plays a crucial role in several applications like surveillance, free biometry, realistic world etc. In this research work, we suggest a new method to track the objects like humans using the motion obtained from color images. This algorithm does not use the object characteristics which is tracked and hence it resembles human eyes that uses the process of tracking in all the available images in RGB. Spatial and temporal association of motions are considered for motion association, which is the proposed plan of action to decrease the undesired selection process. Furthermore, for different images the Wigner distribution has been used which is less dependent on the fluctuation in threshold frame and thus reduces the untrue object detections. The results acquired with this algorithm is identical and consistent which in turn provides the reduction in computational complexity of this algorithm.