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1 July 2010 Robust facial landmark detection for three-dimensional face segmentation and alignment
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Three-dimensional human faces have been applied in many fields, such as face animation, identity recognition, and facial plastic surgery. Segmenting and aligning 3-D faces from raw scanned data is the first vital step toward making these applications successful. However, the existence of artifacts, facial expressions, and noises poses many challenges to this problem. We propose an automatic and robust method to segment and align 3-D face surfaces by locating the nose tip and nose ridge. Taking a raw scanned surface as input, a novel feature-based moment analysis on scale spaces is presented to locate the nose tip accurately and robustly, which is then used to crop the face region. A technique called the geodesic Euclidean ratio is then developed to find the nose ridge. Each face is aligned based on the locations of nose tip and nose ridge. The proposed method is not only invariant to translations and rotations, but also robust in the presence of facial expressions and artifacts such as hair, clothing, other body parts, etc. Experimental results on two large 3-D face databases demonstrate the accuracy and robustness of the proposed method.
©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)
Hai Shan Wu and Yan Qiu Chen "Robust facial landmark detection for three-dimensional face segmentation and alignment," Journal of Electronic Imaging 19(3), 033006 (1 July 2010).
Published: 1 July 2010

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