Paper Title
Efficient Human Object Tracking on Motion Estimation, Background Subtraction and Shadow Removal Technique

Abstract
In this paper we present the technical advances and system development for multiple human Object Tracking On motion estimation, background subtraction and shadow removal technique. It includes technique which corrects errors in the image after shadow removal using a reconstruction process. Most shadow detection and segmentation methods are based on image analysis. Shadow detection and removal in various real life scenarios including indoor our door scenes and computer vision system remained a challenging task. A reference frame is initially used and considered as background information. While a new object enters into the frame, the foreground information and background information are identified using the reference frame as background model. Most of the times, the shadow of the background information is merged with the foreground object and makes the tracking process a complex one. The algorithm involves modeling of the desired background as a reference model for later used in background subtraction to produce foreground pixel which is deviation of the current frame from the reference frame. In the approach morphological operations will be used for identifying and removed the shadow. In our experiments, we evaluate both shadow detection and shadow removal results. For shadow detection the system detects and tracks the moving objects exactly. In this example we covert moving object into frame. Now one frame as a static background is considered thus it may suffer from dynamic scene change such as an extraneous event in which there are new objects deposited into the scene and become part of the background scene. Video sequences will be captured and will be detected with the proposed algorithm. Keywords - Human Motion Estimation, Object Tracking, Shadow Removal, Morphology