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Title:
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Representation and Detection of Shapes in Images |
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Author:
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Felzenszwalb, Pedro F. |
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Issue Date:
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2003-08-08 |
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Abstract:
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We present a set of techniques that can be used to represent anddetect shapes in images. Our methods revolve around a particularshape representation based on the description of objects usingtriangulated polygons. This representation is similar to the medialaxis transform and has important properties from a computationalperspective. The first problem we consider is the detection ofnon-rigid objects in images using deformable models. We present anefficient algorithm to solve this problem in a wide range ofsituations, and show examples in both natural and medical images. Wealso consider the problem of learning an accurate non-rigid shapemodel for a class of objects from examples. We show how to learn goodmodels while constraining them to the form required by the detectionalgorithm. Finally, we consider the problem of low-level imagesegmentation and grouping. We describe a stochastic grammar thatgenerates arbitrary triangulated polygons while capturing Gestaltprinciples of shape regularity. This grammar is used as a prior modelover random shapes in a low level algorithm that detects objects inimages. |
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URI:
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http://hdl.handle.net/1721.1/30400
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Other Identifiers:
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MIT-CSAIL-TR-2003-008
AITR-2003-016 |
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Series/Report no.:
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Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory |
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Keywords:
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AI |
