for Nanotechnology Research and Surveillance System Design by Steven Cheng ( Under the direction of Suchendra

The field of computer vision comprises various disciplines including topics such as background modeling, object tracking, and object detection. The research contained in this manuscript investigates two important aspects of computer vision, namely contour tracking and static object detection. These areas are elements of the more generic process of object analysis. The material discussed within, originated from the requirements of two unique research groups at the University of Georgia. The Nanoscience group in the Physics and Astronomy department required a tracking application for their research on dynamic wettability of nanostructured surfaces. The initial specifications required a software program that could analyze recorded videos of a water droplet spreading on different surfaces fabricated from nanotube arrays. The Contour Tracker utilizes advanced object tracking techniques to track the outer contour of the water droplet. Part I outlines the contour tracking problem and the proposed Contour Tracker solution. The Visual and Parallel Computing Lab has many projects in their repertoire including research on surveillance and monitoring system design. A common goal of surveillance systems is to detect stationary objects within the scene. A static object could indicate several scenarios depending on the location of the scene. For instance, an idle object in an airport may be someone’s forgotten luggage or worse, an explosive device, whereas static objects on the side of the street could indicate an illegally parked vehicle. Part II describes a simple and flexible method for static object detection. Index words: Active Contours, Snakes, Kalman Snake, Contour Tracking, Multiscale Background Model, Static Object Detection, Surveillance System Computer Vision Applications for Nanotechnology Research and Surveillance System Design