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Vectorizing Face Images by Interpreting Shape and Texture Computations

dc.date.accessioned2004-10-08T20:36:06Z
dc.date.accessioned2018-11-24T10:21:21Z
dc.date.available2004-10-08T20:36:06Z
dc.date.available2018-11-24T10:21:21Z
dc.date.issued1995-09-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/6641
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/6641
dc.description.abstractThe correspondence problem in computer vision is basically a matching task between two or more sets of features. In this paper, we introduce a vectorized image representation, which is a feature-based representation where correspondence has been established with respect to a reference image. This representation has two components: (1) shape, or (x, y) feature locations, and (2) texture, defined as the image grey levels mapped onto the standard reference image. This paper explores an automatic technique for "vectorizing" face images. Our face vectorizer alternates back and forth between computation steps for shape and texture, and a key idea is to structure the two computations so that each one uses the output of the other. A hierarchical coarse-to-fine implementation is discussed, and applications are presented to the problems of facial feature detection and registration of two arbitrary faces.en_US
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dc.format.extent921596 bytes
dc.language.isoen_US
dc.titleVectorizing Face Images by Interpreting Shape and Texture Computationsen_US


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