Object detection and tracking based on silhouette based trained shape model with Kalman filter

Object detection and tracking plays an important role in the field of video surveillance and has been discussed since many years. There are several techniques available in literature. But to find out a robust method which can give the better result is a challenging job. In this paper, we proposed a method which can detect and track the motion of an object. The proposed method is a combination of adaptive background subtraction, a trained silhouette based model for detection and Kalman filter for tracking purpose.