Moving Object Detection with Moving Background using Optic Flow

In recent scenario, video surveillance systems are important to monitor security sensitive areas such as banks, crowded public places and borders. Hence, Object detection in such video surveillance is an important task. Research work to detect an object with steady background is carried out and upto some extent it is easy but with moving background it is still challenging. Object detection is complicated as the camera motion and object motion are mixed. Motion vectors, represents flow of a moving object, are obtained using Lucas - kanade optical flow algorithm for moving object detection with complex background. These flow vectors are quantized using a predefined threshold to decide whether a pixel is a part of an object or a background. We have used bilateral filter as a pre-processing step due to which accurate and fast detection of the object is achieved.