Contour Tracking of Targets with Large Aspect Change

Abstract

In this paper we present a novel method for tracking contour of a moving rigid object in natural video sequences from a mobile camera. While a mobile camera is keeping track of a moving target, any change in relative orientation or position of the target and camera may cause a change in the view of target captured by the camera. This is called the target aspect change and known as a challenge in tracking. Especially, a large aspect change may reveal some previously hidden parts of the target, and this is the case we have handled in our algorithm. In proposed contour tracking method the motion model of the target is estimated using corner matching and LMedS statistical method. This model is used together with an active contour (snake) to track the target efficiently. The snake we propose is capable of swelling locally, so that it can swell and include newly appeared parts of the target in case of a large aspect change. Detecting target newly appeared parts, is based on the fact that a part of target should move consistently with other parts and inconsistently with the background. When a new part is detected the nearby part of the snake is stimulated to swell. In this way the snake will include any new part of the target revealed by a large aspect change. Several experiments have been conducted to show the promise of proposed algorithm.