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The Template Update Problem
I. Matthews, T. Ishikawa, and S. Baker
Proceedings of the British Machine Vision Conference, September, 2003.

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Template tracking is a well studied problem in computer vision which dates back to the Lucas-Kanade algorithm of 1981. Since then the paradigm has been extended in a variety of ways including: arbitrary parametric transformations of the template, and linear appearance variation. These extensions have been combined, culminating in non-rigid appearance models such as Active Appearance Models (AAMs) and Active Blobs. One question that has received very little attention is how to update the template over time so that it remains a good model of the object being tracked. This paper proposes an algorithm to update the template that avoids the "drifting" problem of the naive update algorithm. Our algorithm can be interpreted as a heuristic to avoid local minima. It can also be extended to templates with linear appearance variation. This extension can be used to convert (update) a generic, person-independent AAM into a person specific AAM.

Sponsor: Denso Corporation, US Department of Defense
Grant ID: N41756-03-C4024

Associated center: VASC
Associated labs/groups: Face Group and Vision for Safe Driving
Associated projects: Template Update, Face Model Building and Fitting, and Car Tracking

I. Matthews, T. Ishikawa, and S. Baker, "The Template Update Problem," Proceedings of the British Machine Vision Conference, September, 2003.

@inproceedings{Matthews_2003_4433,
   author = "Iain Matthews and Takahiro Ishikawa and Simon Baker",
   title = "The Template Update Problem",
   booktitle = "Proceedings of the British Machine Vision Conference",
   month = "September",
   year = "2003"
}