Generic active appearance models revisited

Tzimiropoulos, Georgios and Alabort-i-Medina, Joan and Zafeiriou, Stefanos and Pantic, Maja (2013) Generic active appearance models revisited. Lecture Notes in Computer Science, 7726 . pp. 650-663. ISSN 0302-9743

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Abstract

The proposed Active Orientation Models (AOMs) are generative models of facial shape and appearance. Their main differences with the well-known paradigm of Active Appearance Models (AAMs) are (i) they use a different statistical model of appearance, (ii) they are accompanied by a robust algorithm for model fitting and parameter estimation and (iii) and, most importantly, they generalize well to unseen faces and variations. Their main similarity is computational complexity. The project-out version of AOMs is as computationally efficient as the standard project-out inverse compositional algorithm which is admittedly the fastest algorithm for fitting AAMs. We show that not only does the AOM generalize well to unseen identities, but also it outperforms state-of-the-art algorithms for the same task by a large margin. Finally, we prove our claims by providing Matlab code for reproducing our experiments.

Item Type: Article
Additional Information: Chapter in: Computer Vision – ACCV 2012 : 11th Asian Conference on Computer Vision, Daejeon, Korea, November 5-9, 2012, revised selected papers, Part III. ISBN 978-3-642-37430-2
Schools/Departments: University of Nottingham UK Campus > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1007/978-3-642-37431-9_50
Depositing User: Tzimiropoulos, Yorgos
Date Deposited: 01 Feb 2016 09:28
Last Modified: 14 Sep 2016 22:07
URI: http://eprints.nottingham.ac.uk/id/eprint/31430

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