Level Set Methods in an EM Framework for Shape Classification and Estimation
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Overview: This paper proposes an Expectation-Maximization approach to separate a shape database into different shape classes, while simultaneously estimating the shape contours that best exemplify each of the different shape classes. They begin their formulation by employing the level set function as the shape descriptor. Next, for each shape class they assume that there exists an unknown underlying level set function whose zero level set describes the contour that best represents the shapes within that shape class. The level set function for each example shape is modeled as a noisy measurement of the appropriate shape class's unknown underlying level set function.
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Format: PDF | Size: 350KB | Date: Aug 2004 | Pages: 9
