Moving object tracking using active models

We propose a model based tracking algorithm which can extract trajectory information of a target object by detecting and tracking a moving object from a sequence of images. The algorithm constructs a model from the detected moving object and match the model with successive image frames to track the target object. We use an active model which characterizes regional and structural features of a target object such as shape, texture, color, and edge. Our active model can adapt itself dynamically to an image sequence so that it can track a non-rigid moving object. Such an adaptation is made under the framework of energy minimization. We design an energy function so that the function can embody structural attributes of a target as well as its spectral attributes. We applied a Kalman filter to predict motion information. The predicted motion information by Kalman filter was used very efficiently to reduce the search space in the matching process.