Detecting & Tracking Of Moving Object In Video Sequence In Complex Scene

The thesis is focused on the technique of detection and tracking of the moving objects in image sequences. Detection and tracking of moving objects in image sequences is one of the most important research topics in the domain of computer vision, it is also an active field which has interested many researchers in recent years. It has applications in smart surveillance system, virtual reality, advanced user interface, motion analysis, model-based coding and so on.The research interest of moving objects detection and tracking is video sequence, i.e. sequence. Object detection in videos involves verifying the presence of an object in image sequences and possibly locating it precisely. Object tracking is to monitor an object's spatial and temporal changes during a video sequence, including its presence, position, size, shape, etc. These two processes are closely related because tracking usually starts with detecting objects, while detecting an object repeatedly in subsequent image sequence is often necessary to verify tracking.The major work implemented in this paper is presented as follows:1. For a video sequence, moving change regions are achieved firstly by means of converting difference image to binary image using thresholding and morphological filtering, then can obtain the moving object.2. A preliminary investigation is made into moving objects tracking. This article presents an algorithm to track moving objects based on Kalman filtering, propose the method that combining shape feature with nearest neighboring on the improvement of kalman filter can only track single object of fixed size and shape. This method can satisfy real-time demands, its tracking effect is famous at the same time.