Real time objects detection and positioning in multiple regions using single fixed camera view for video surveillance applications

Abstract

Detection of objects precisely in video surveillance system is vital for many applications such as abnormal activity detection, congestion analysis, person identification, military fields. For detection of objects, background subtraction and temporal detection methods are used. In background subtraction method moving and static objects which enters into a camera viewing region has been detected. In this method reference frame will be captured during camera initialization. It uses a reference frame as background, detects present frame and takes the difference between two frames. In this paper objects are detected in multiple regions separately from single camera instead of using multiple cameras to monitor different objects in different regions. And also user will have control to select required single or multiple regions to detect the object. This will reduces the overall cost of the system and increases the processing speed of the system if we choose a particular region. Accuracy of the object detection in different regions increases since it allows using different parameters like thresholding separately. So that it monitors different activities at the same time. Also detection of objects based on comparison, object of interest from stored data base is presented using single static camera view with good real time performance.