DMCA
Facial Features Segmentation by Model-Based Snakes (1995)
| Venue: | In International Conference on Computing Analysis and Image Processing |
| Citations: | 4 - 0 self |
BibTeX
@INPROCEEDINGS{Radeva95facialfeatures,
author = {Petia Radeva and Enric Martí},
title = {Facial Features Segmentation by Model-Based Snakes},
booktitle = {In International Conference on Computing Analysis and Image Processing},
year = {1995}
}
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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. 1 Introduction The successful automatic extraction of facial features is strongly dependent on the existance of feature model that should be descriptive enough to embody common s...
Keyphrases
facial feature segmentation deformable model model-based snake facial image rubber snake feature model successful automatic extraction significant improvement facial snapshot detected feature shape segment different feature good approximation natural representation facial segmentation free natural feature shape active contour model facial feature segmentation process reduced computational cost numerous weigths standard technique
