We present an object tracking system based on an edge model for the target characterization. The target position is estimated by looking for the model in the current image using a Hausdorff partial distance. Target is searched only in a sub-window of current edge image. Its boundaries are determined by a Kalman filter estimation that uses target dynamics to predict current position. We use a spiral searching strategy to find the actual position. The target model is updated in each iteration by using unidirectional partial distance from the image to the model. An enclosure operator refines this model in order to perform the target/ background discrimination. The parameters of our system can be modified in an active way along the tracking task. The system has shown to be robust to illumination changes and to pose variations. The system has been also embedded in a mobile robot for personal robotics applications and integrated in a real-time OS (3 Hz).