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Automatic Detection of Facial Midline And Its Contributions To Facial Feature Extraction
Nakao, Nozomi (Mie University (Japó). Graduate School of Engineering)
Ohyama, Wataru (Mie University (Japó). Graduate School of Engineering)
Wakabayashi, Tetsushi (Mie University (Japó). Graduate School of Engineering)
Kimura, Fumitaka (Mie University (Japó). Graduate School of Engineering)

Date: 2007
Abstract: We propose a novel approach for detection of the facial midline from a frontal face image. Using midline as a guide reduces computational cost required for facial feature extraction (FFE) because the midline is capable of restricting multi-dimensional searching process into one-dimensional search. The proposed method detects the facial midline from an edge image as the symmetry axis using the generalized Hough transformation. Experimental results on the FERET database indicate that the proposed algorithm can accurately detect facial midlines over many different scales and rotation. The total computational time for facial feature extraction has been reduced by a factor of 280 using the midline detected by this method.
Rights: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Language: Anglès
Document: Article ; recerca ; Versió publicada
Subject: Mitja línia facial ; Detecció de característica facial ; Media línea facial ; Detección de característica facial ; Facial midline ; Facial feature detection ; Generalized Hough transformation ; Biometrics
Published in: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 6 n. 3 (2007) p. 55-65, ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.es/article/view/v6-n3-ohyama-nakao-wakabayashi-et-al
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/85534
DOI: 10.5565/rev/elcvia.142


12 p, 1.1 MB

The record appears in these collections:
Articles > Published articles > ELCVIA
Articles > Research articles

 Record created 2008-03-28, last modified 2022-02-19



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