Detection and Tracking of Moving Object Based on Background Subtracion

The proposed work presents a survey on moving object detection and tracking methods. It is classified into different categories and new trends identify. This work shows moving object detection and tracking using different and efficient methodologies. Object detection and object tracking is used to track the object type(such as human, vehicles) and detect the movement of the object(such as moving, standing).This survey shows various methodologies for object detection and tracking such as background subtraction, background modelling, intensity range based background subtraction. A new tracking method that uses Three Temporal Difference (TTD) and the Gaussian Mixture Model (GMM) approach for object tracking. TTD method is the use of a continuous image subtraction. The GMM approach consists of three different Gaussian distributions, the average, standard deviation and weight respectively. There are two important steps to establish the background for model, and background updates which separate the foreground and background. This paper combines the TTD and GMM object tracking. The simulated result shows that used methodologies for effective object detection has better accuracy and with less processing time consumption rather than existing