|We present a novel approach to tracking planar surface patches over time. In addition to tracking a patch with full six degrees of freedom, the algorithm also produces a super-resolved estimate of the texture present on the patch. This texture estimate is kept as an explicit model texture image which is refined over time. We then use it to infer the 3D motion of the patch from the image sequence.
The main idea behind the approach is to use a technique from computer graphics, known as texture mapping, as the measurement model in an extended Kalman filter. We also calculate the partial derivative of this image formation process with respect to the 3D pose of the patch, which functions as the measurement Jacobian. The super-resolved estimate of the texture is obtained using the standard extended Kalman filter measurement update, with one essential approximation that makes this computationally feasible. The resulting equations are remarkably simple, yet lead to estimates that are properly super-resolved.
In addition to developing the theory behind the approach, we also demonstrate both the tracking and the super-resolution aspect of the algorithm on real image sequences.
|Frank Dellaert, Chuck Thorpe, and Sebastian Thrun, "Super-Resolved Texture Tracking of Planar Surface Patches," IEEE/RSJ International Conference on Intelligent Robotic Systems, October, 1998.|
author = "Frank Dellaert and Chuck Thorpe and Sebastian Thrun",
title = "Super-Resolved Texture Tracking of Planar Surface Patches",
booktitle = "IEEE/RSJ International Conference on Intelligent Robotic Systems",
month = "October",
year = "1998",
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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