Abstract
The performance of human face recognition algorithms is seriously affected by two important factors: head pose and lighting condition. The effective processing of the pose and illumination variations is a vital key for improving the recognition rate. This paper proposes a novel method that can synthesize images with different head poses and lighting conditions by using a modified 3D CANDIDE model, linear vertex interpolation and NURBS curve surface fitting method, as well as a mixed illumination model. A specific Eigenface method is also proposed to perform face recognition based on a pre-estimated head pose method. Experimental results show that the quality of the synthesized images and the recognition performance are good.
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Liu, Dh., Shen, Ls., Lam, Km. (2005). Image Synthesis and Face Recognition Based on 3D Face Model and Illumination Model. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_2
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DOI: https://doi.org/10.1007/11539117_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28325-6
Online ISBN: 978-3-540-31858-3
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