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A novel FNP-pose estimation for three-dimensional face recognition using DPCA under facial expression

Lookup NU author(s): June Youn Hwang, Dr Wai Lok Woo, Emeritus Professor Satnam Dlay

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Abstract

This paper presents an efficient 3D face recognition algorithm with facial expression. The proposed algorithm describes a novel FNP (Fast Nose Points) -Pose Estimation which is the Triangle-based four point method to estimate the pose of three-dimensional (3-D) face, (i.e. the 3-D shape). Firstly, we find the specific points using Angle comparison Trace. Secondly, from this triangle we calculate weight point of triangle which is used for translation and compensate the rotation of 3D test facial image. Finally, 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 and segment 2-by-2 around this point. The proposed algorithm allows the use of fast iterative algorithm to compute the 3-D facial pose and 3D face recognition that best fits the data. The algorithm has been tested with 3D database and obtained results provide a high level of robustness and accurate recognition. © 2007 IEEE.


Publication metadata

Author(s): Hwang J, Woo WL, Dlay SS

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 15th International Conference on Digital Signal Processing, DSP 2007

Year of Conference: 2007

Pages: 235-239

Publisher: Institute of Electrical and Electronics

DOI: 10.1109/ICDSP.2007.4288562

Library holdings: Search Newcastle University Library for this item

ISBN: 1424408822


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