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. Author manuscript; available in PMC: 2010 Jul 8.
Published in final edited form as: Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit. 2008 Jun 23;2008:1–8. doi: 10.1109/CVPR.2008.4587808

Figure 3.

Figure 3

A comparison of results using the MultiPIE face database [10]. 125 subjects were included in the training set and the other 125 subjects were used for testing. The initial shape error was between 5 – 10 pixels RMS-PE. The following four methods were included in the comparison: (i) the exhaustive local search (ELS), (ii) the convex quadratic fitting (CQF) method, (iii) the robust convex quadratic fitting (RCQF) and (iv) the active appearance model (AAM) method. As we can see, the CLM methods all outperformed the holistic AAM method by higher alignment accuracy and larger convergence rates. Moreover, the proposed CQF and RCQF methods had further improved the alignment performance of the ELS method. The RCQF method shows the best performance among all alignment methods.