Zoom tracking

In this paper we present a new active vision technique called zoom tracking. Zoom tracking is the continuous adjustment of a camera´s focal length, to keep a constant-sized image of an object moving along the camera´s optical axis. Two methods for performing zoom tracking are presented: a closed-loop visual feedback algorithm based on optical flow, and use of depth information obtained from an autofocus camera´s range sensor. We show that the image stability provided by zoom tracking improves the performance of algorithms that are scale variant, such as correlation-based trackers. While zoom tracking cannot totally compensate an object´s motion, due to the effect of perspective distortion, an analysis of this distortion provides a quantitative estimate of the performance of zoom tracking