Optimization problems for fast AAM fitting in-the-wild

Tzimiropoulos, Georgios and Pantic, Maja (2013) Optimization problems for fast AAM fitting in-the-wild. In: 2013 IEEE International Conference on Computer Vision (ICCV), 2-8 Dec 2013, Sydney, Australia.

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We describe a very simple framework for deriving the most-well known optimization problems in Active Appearance Models (AAMs), and most importantly for providing efficient solutions. Our formulation results in two optimization problems for fast and exact AAM fitting, and one new algorithm which has the important advantage of being applicable to 3D. We show that the dominant cost for both forward and inverse algorithms is a few times mN which is the cost of projecting an image onto the appearance subspace. This makes both algorithms not only computationally realizable but also very attractive speed-wise for most current systems. Because exact AAM fitting is no longer computationally prohibitive, we trained AAMs in-the-wild with the goal of investigating whether AAMs benefit from such a training process. Our results show that although we did not use sophisticated shape priors, robust features or robust norms for improving performance, AAMs perform notably well and in some cases comparably with current state-of- the-art methods. We provide Matlab source code for training, fitting and reproducing the results presented in this paper at http://ibug.doc.ic.ac.uk/resources.

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/1005671
Additional Information: (c) 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Tzimiropoulos, Yorgos
Date Deposited: 29 Jan 2016 11:50
Last Modified: 04 May 2020 20:20
URI: https://eprints.nottingham.ac.uk/id/eprint/31433

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