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Local Minima Free Parameterized Appearance Models

Local Minima Free Parameterized Appearance Models

This video was recorded at Carnegie Mellon Machine Learning Lunch seminar. Parameterized Appearance Models (PAMs) (e.g. Eigen-tracking, Active Appearance Models, Morphable Models) are commonly used to model the appearance and shape variation of objects in images. While PAMs have numerous advantages relative to alternate approaches, they have at least two drawbacks. First, they are especially prone to local minima in the fitting process. Second, often few if any of the local minima of the cost function correspond to acceptable solutions. To solve these problems, this paper proposes a method to learn a cost function by explicitly optimizing that the local minima occur at and only at the places corresponding to the correct fitting parameters. To the best of our knowledge, this is the first... Show More
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