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@ -60,7 +60,7 @@ the euclidean distance between feature vectors of a probe and reference image. S |
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robust against changes in illumination by its nature, but has a huge drawback: the accurate |
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registration of the marker points is complicated, even with state of the art algorithms. Some of the |
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latest work on geometric face recognition was carried out in @cite Bru92 . A 22-dimensional feature |
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vector was used and experiments on large datasets have shown, that geometrical features alone my not |
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vector was used and experiments on large datasets have shown, that geometrical features alone may not |
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carry enough information for face recognition. |
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The Eigenfaces method described in @cite TP91 took a holistic approach to face recognition: A facial |
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