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Active appearance model

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This is an old revision of this page, as edited by TimSC (talk | contribs) at 11:18, 19 August 2012 (AAM-API is not open source by the OSI definition (No Discrimination Against Fields of Endeavor)). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

An active appearance model (AAM) is a computer vision algorithm for matching a statistical model of object shape and appearance to a new image. They are built during a training phase. A set of images, together with coordinates of landmarks that appear in all of the images, is provided to the training supervisor.

The approach is widely used for matching and tracking faces and for medical image interpretation.

The algorithm uses the difference between the current estimate of appearance and the target image to drive an 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 landmarks), and does not take advantage of all the available information – the texture across the target object. This can be modelled using an AAM.

  • Free Tools for experimenting with AAMs from Manchester University (for research use only).
  • Description of AAMs from Manchester University.
  • Tim Cootes' home page (one of the original co-inventors of AAMs).
  • Mikkel B. Stegmann's home page of AAM-API, C++ AAM implementation (non-commerical use only).
  • Original Active Appearance Model Open-source Matlab implementation
  • [1] AAMtools: An Active Appearance Modeling Toolbox
  • [2] FaceTracker, free for research purposes only.
  • [3] Open Tracking Library.

Some reading

  • Edwards G, Taylor C, Cootes T. Interpreting face images using active appearance models Proceeding of the International Conference on Face And Gesture Recognition 1998, pages 300-305 (first publication of AAM algorithm)
  • T. F. Cootes, G. J. Edwards, and C. J. Taylor. Active appearance models. IEEE TPAMI, 23(6):681–685, 2001
  • T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham. 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. 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[pdf]
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