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The model was first introduced by Edwards, Cootes and Taylor in the context of face analysis at the 3rd International Conference on Face and Gesture Recognition, 1998.<ref>{{Cite book | last1 = Edwards | first1 = G. J. | last2 = Taylor | first2 = C. J. | last3 = Cootes | first3 = T. F. | doi = 10.1109/AFGR.1998.670965 | chapter = Interpreting face images using active appearance models | title = Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition | pages = 300 | year = 1998 | isbn = 978-0-8186-8344-2 | citeseerx = 10.1.1.33.1784 | s2cid = 11269423 }}</ref> Cootes, Edwards and Taylor further described the approach as a general method in computer vision at the European Conference on Computer Vision in the same year.<ref>{{Cite book | last1 = Cootes | first1 = T. F. | last2 = Edwards | first2 = G. J. | last3 = Taylor | first3 = C. J. | doi = 10.1007/BFb0054760 | chapter = Active appearance models | title = Computer Vision — ECCV'98 | series = Lecture Notes in Computer Science | volume = 1407 | pages = 484 | year = 1998 | isbn = 978-3-540-64613-6 | citeseerx = 10.1.1.374.7954 | s2cid = 2230657 }}</ref><ref>{{Cite journal | last1 = Cootes | first1 = T. F. | last2 = Edwards | first2 = G. J. | last3 = Taylor | first3 = C. J. | doi = 10.1109/34.927467 | title = Active appearance models | journal = IEEE Transactions on Pattern Analysis and Machine Intelligence | volume = 23 | issue = 6 | pages = 681 | year = 2001 | citeseerx = 10.1.1.128.4967 }}</ref> The approach is widely used for [[face tracking|matching and tracking faces]] and for [[medical imaging|medical image interpretation]].
The algorithm uses the difference between the current estimate of appearance and the target image to drive an [[Optimization (mathematics)|optimization]] process.
By taking advantage of the [[least squares]] techniques, it can match to new images very swiftly.
It is related to the [[active shape model]] (ASM). One disadvantage of ASM is that it only uses shape constraints (together with some information about the image structure near the [[Landmark point|landmarks]]), and does not take advantage of all the available information – the texture across the target object. This can be modelled using an AAM.
==References==
{{Reflist}}
==External links==▼
* [http://www.isbe.man.ac.uk/~bim/software/am_tools_doc/index.html Free Tools] for experimenting with AAMs from Manchester University.▼
* [http://www.isbe.man.ac.uk/~bim//Models/index.html Description] of AAMs from Manchester University.▼
== Some reading ==
[[Category:Computer vision]]▼
* T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham. [https://pdfs.semanticscholar.org/e8f2/e06238ecd873b044740e9e95dd7592feb139.pdf Training models of shape from sets of examples]. ''In Proceedings of BMVC'92, pages 266–275, 1992''
* S. C. Mitchell, J. G. Bosch, B. P. F. Lelieveldt, R. J. van der Geest, J. H. C. Reiber, and M. Sonka. [https://perso.telecom-paristech.fr/angelini/MIMED/papers_2010/mitchell_tmi_2002.pdf 3-d active appearance models: Segmentation of cardiac MR and ultrasound images]. ''IEEE Trans. Med. Imaging, 21(9):1167–1178, 2002''
* T.F. Cootes, G. J. Edwards, and C. J. Taylor. Active appearance models. ECCV, 2:484–498, 1998[https://www.cs.cmu.edu/~efros/courses/AP06/Papers/cootes-eccv-98.pdf [pdf<nowiki>]</nowiki>]
▲==External links==
▲* [http://
▲* [http://
* [http://www2.imm.dtu.dk/~aam/ IMM AAM Code] Dr Mikkel B. Stegmann's home page of AAM-API, C++ AAM implementation (non-commercial use only).
* [http://www.mathworks.com/matlabcentral/fileexchange/26706-active-shape-model-asm-and-active-appearance-model-aam Matlab AAM Code] Open-source Matlab implementation of the original AAM algorithm.
* [http://cvsp.cs.ntua.gr/software/AAMtools/ AAMtools] An Active Appearance Modelling Toolbox in Matlab by Dr George Papandreou.
* [https://web.archive.org/web/20150122191259/http://staff.estem-uc.edu.au/roland/research/demolib-home/ DeMoLib] AAM Toolbox in C++ by Dr Jason Saragih and Dr Roland Goecke.
▲[[Category:Computer vision]]
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