3D Model Based Pose Invariant Face Recognition from a Single Frontal View
Chen, Qinran (The Chinese University of Hong Kong. Department of Electronic Engineering)
Cham, Wai-kuen (The Chinese University of Hong Kong. Department of Electronic Engineering)

Fecha:	2007
Resumen:	This paper proposes a 3D model based pose invariant face recognition method that can recognize a face of a large rotation angle from its single nearly frontal view. The proposed method achieves the goal by using an analytic-to-holistic approach and a novel algorithm for estimation of ear points. Firstly, the proposed method achieves facial feature detection, in which an edge map based algorithm is developed to detect the ear points. Based on the detected facial feature points 3D face models are computed and used to achieve pose estimation. Then we reconstruct the facial feature points' locations and synthesize facial feature templates in frontal view using computed face models and estimated poses. Finally, the proposed method achieves face recognition by corresponding template matching and corresponding geometric feature matching. Experimental results show that the proposed face recognition method is robust for pose variations including both seesaw rotations and sidespin rotations.
Derechos:	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.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Face Recognition ; Pose Estimation ; 3D face Model ; Single View ; Reconeixement de cara ; Model de cara 3D ; Vista única ; Reconocimiento de cara ; Modelo de cara 3D
Publicado en:	ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 6 n. 1 (2007) p. 13-26, ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.es/article/view/v6-n1-chen-cham
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/85556
DOI: 10.5565/rev/elcvia.134

14 p, 544.7 KB

El registro aparece en las colecciones:
Artículos > Artículos publicados > ELCVIA
Artículos > Artículos de investigación