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Author Petia Radeva; Enric Marti
Title Facial Features Segmentation by Model-Based Snakes Type Conference Article
Year 1995 Publication International Conference on Computing Analysis and Image Processing Abbreviated Journal
Volume Issue Pages
Keywords (down)
Abstract Deformable models have recently been accepted as a standard technique to segment different features in facial images. Despite they give a good approximation of the salient features in a facial image, the resulting shapes of the segmentation process seem somewhat artificial with respect to the natural feature shapes. In this paper we show that active contour models (in particular, rubber snakes) give more close and natural representation of the detected feature shape. Besides, using snakes for facial segmentation frees us from the problem of determination of the numerous weigths of deformable models. Another advantage of rubber snakes is their reduced computational cost. Our experiments using rubber snakes for segmentation of facial snapshots have shown a significant improvement compared to deformable models.
Corporate Author Thesis
Publisher Place of Publication Bellaterra (Barcelona), Spain Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
Area Expedition Conference
Notes MILAB;IAM Approved no
Call Number IAM @ iam @ RAM1995a Serial 1633
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