Automatic face segmentation and facial landmark detection in range images

We present a methodology for face segmentation and facial landmark detection in range images. Our goal was to develop an automatic process to be embedded in a face recognition system using only depth information as input. To this end, our segmentation approach combines edge detection, region cluster...

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Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society. - 1996. - 40(2010), 5 vom: 04. Okt., Seite 1319-30
1. Verfasser: Pamplona Segundo, Maurício (VerfasserIn)
Weitere Verfasser: Silva, Luciano, Bellon, Olga Regina Pereira, Queirolo, Chauã C
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2010
Zugriff auf das übergeordnete Werk:IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
Beschreibung
Zusammenfassung:We present a methodology for face segmentation and facial landmark detection in range images. Our goal was to develop an automatic process to be embedded in a face recognition system using only depth information as input. To this end, our segmentation approach combines edge detection, region clustering, and shape analysis to extract the face region, and our landmark detection approach combines surface curvature information and depth relief curves to find the nose and eye landmarks. The experiments were performed using the two available versions of the Face Recognition Grand Challenge database and the BU-3DFE database, in order to validate our proposed methodology and its advantages for 3-D face recognition purposes. We present an analysis regarding the accuracy of our segmentation and landmark detection approaches. Our results were better compared to state-of-the-art works published in the literature. We also performed an evaluation regarding the influence of the segmentation process in our 3-D face recognition system and analyzed the improvements obtained when applying landmark-based techniques to deal with facial expressions
Beschreibung:Date Completed 25.01.2011
Date Revised 15.09.2010
published: Print-Electronic
Citation Status MEDLINE
ISSN:1941-0492
DOI:10.1109/TSMCB.2009.2038233