Moving Object Detection and Tracking for Video Surveillance: A Review

This paper presents a review and systematic study on the moving object detection and surveillance of the video as it is an important and challenging task in many computer vision applications, such as human detection, vehicles detection, threat, and security. Video surveillance is a dynamic environment, especially for human and vehicles and for specific object in case of security is one of the current challenging research topics in computer vision. It is a key technology to fight against terrorism, crime, public safety and for efficient management of accidents and crime scene going on now days. The paper also presents the concept of real time implementation computing task in video surveillances system. In this review paper various methods are discussed were evaluation of order to access how well they can detect moving object in an outdoor/indoor section in real time situation

Advanced Moving Object Detection and Tracking for Video Surveillance

Moving object detection is a very crucial and challenging task in computer vision applications such as surveillance, vehicle and human tracking. Background subtraction is a preliminary technique widely used for the moving object detection. In this paper, an advanced automated moving object detection technique using background subtraction is proposed. The method uses running average wavelet transform (RAWT) for accurate registration of background from the video sequence. Furthermore, the moving objects are detected by comparing current and background frame. In order to produce higher accuracy for the object detection, the proposed method also further includes post-processing filter operation after which the binary object detection mask can be obtained. After moving object detection, tracking is performed. Experimental results demonstrate that the proposed method is faster and efficient as compared to the other state-of-the-art existing methods