Abstract
Accurate and robust location of feature point is a difficult and challenging issue in face recognition. In this paper we propose a new approach of using a cascade of Multi-Resolution Active Shape Models (C-MR-ASM) to locate facial feature points. In our approach, more than one MR-ASMs are obtained from different subsets of training set automatically, and these MR-ASMs are integrated in a cascade to locate facial feature points. Experimental results show that our algorithm is more accurate than traditional MR-ASM. The contribution of this paper includes: 1, unlike traditional MR-ASM, the training set is divided into several subsets automatically based on the principle a trained model should describe all the samples in training set accurately. 2, we propose the new cascade framework, which integrates all the subset MR-ASM.
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Zhang, S., Wu, L., Wang, Y. (2007). Cascade MR-ASM for Locating Facial Feature Points. In: Lee, SW., Li, S.Z. (eds) Advances in Biometrics. ICB 2007. Lecture Notes in Computer Science, vol 4642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74549-5_72
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DOI: https://doi.org/10.1007/978-3-540-74549-5_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74548-8
Online ISBN: 978-3-540-74549-5
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