|Title:||Zoom Tracking and its Applications
|Authors:||Jeffrey A. Fayman, Oded Sudarsky, Ehud Rivlin
|Abstract:||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 explore two uses of zoom tracking: improving the performance of scale variant algorithms, and recovery of depth information. 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 quatitative estimate of the performance of zoom tracking. zoom tracking can be used to reconstruct a depth map of tracked object. We show that under normal circumstances this reconstruction is much more accurate than depth from zooming, and works over a greater range than depth from axial motion while providing only slightly less accurate results.|
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