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Vectorizing Face Images by Interpreting Shape and Texture Computations

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dc.creator Beymer, David
dc.date 2004-10-08T20:36:06Z
dc.date 2004-10-08T20:36:06Z
dc.date 1995-09-01
dc.date.accessioned 2013-10-09T02:46:20Z
dc.date.available 2013-10-09T02:46:20Z
dc.date.issued 2013-10-09
dc.identifier AIM-1537
dc.identifier http://hdl.handle.net/1721.1/6641
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description The 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.
dc.format 2729286 bytes
dc.format 921596 bytes
dc.format application/postscript
dc.format application/pdf
dc.language en_US
dc.relation AIM-1537
dc.title Vectorizing Face Images by Interpreting Shape and Texture Computations


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