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Lookup NU author(s): June Youn Hwang,
Dr Wai Lok Woo,
Professor Satnam Dlay
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Biometric identification especially in 3D face recognition is on newer stage due to technical advances. However, large 3D data makes heavy computation. This paper presents an efficient 3D face recognition algorithm which finds nose points fast in order to align face pose and makes fast mean rotation (CDMMR). We find the specific nose points using Corner Detection Method. In addition, we introduce Mean Rotation to rotate pose fast. Depth PCA is employed for 3D face recognition where it performs PCA on a 2D x-y axis and takes into account the depth information from 3D Vertices and Face entries. 2D texture information is mapped corresponding to each point at centre of vertices. This algorithm allows the use of fast iterative algorithm to compute the 3-D facial pose and 3D face recognition that best fits the data. This algorithm provides best result with robust and accuracy.
Author(s): Hwang JY, Woo WL, Dlay SS
Editor(s): Erich Leitgeb; Wolfgang Kogler; Zabih Ghassemlooy
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 6th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP 2008)
Year of Conference: 2008
Publisher: Graz University of Technology
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