Abstract
2D face recognition is held back because the face is three-dimensional. The 3D facial data can provide a promising way to understand the feature of the human face in 3D space and has potential possibility to improve the performance of the system. There are some distinct advantages in using 3D information: sufficient geometrical information, invariance of measured features relative to transformation and capture process by laser scanners being immune to illumination variation. A 3D face recognition method based on geometrical measurement is proposed. By two ways, the 3D face data can be obtained, then their facial feature points are extracted and the measurement is done. A feature vector is composed of eleven features. Self-Recognition and Mutual-Recognition are tested. The results show that the presented method is feasible.
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Zhou, M., Liu, X., Geng, G. (2004). 3D Face Recognition Based on Geometrical Measurement. In: Li, S.Z., Lai, J., Tan, T., Feng, G., Wang, Y. (eds) Advances in Biometric Person Authentication. SINOBIOMETRICS 2004. Lecture Notes in Computer Science, vol 3338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30548-4_28
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DOI: https://doi.org/10.1007/978-3-540-30548-4_28
Publisher Name: Springer, Berlin, Heidelberg
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