Proximity Approach for Object Detection in Video
Last decade we are experiencing more applications in video surveillance to address issues related to social needs. As public concern about crime and terrorist activity increases, the importance of public security is growing, and video surveillance systems are increasingly widespread tools for monitoring, management, and law enforcement in public areas. Object detection is a primary concern about all of these applications domains.
In this paper, we exploit computer vision methods to detect moving object from video to track in real time as objects encountered in the indoor and outdoor environment. Proximity is a fact of being near to other and justifies closeness. These concepts of object being close to each other is checked while the process of object tracking. System tracks assorted objects against an environment consisting of objects of varying sizes, shapes and colors. Initially background modeling is performed using the function which accumulated the background frames from mean and standard deviation of first N frames. Each significant change in the object appearance thereafter, due to new object, old object disappearance is tracked based on the proximity of the target object. The visual resemblance is determined with respect to the detected object in the previous video frame and the last frame captures.