Proceedings Article10.1109/ICPR.2006.207
Active Feature Models
Georg Langs,Philipp Peloschek,René Donner,Michael Reiter,Horst Bischof +4 more
- 20 Aug 2006
- Vol. 1, pp 417-420
TL;DR: Experimental results and the comparison to AAMs on different data sets indicate that active feature models can improve search speed and result accuracy, considerably.
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Abstract: In this paper active feature models are proposed. They utilize local texture features and a statistical shape model for the reliable localization of landmarks in images. They are related to active appearance models, but instead of modelling the entire texture of an object they represent image texture by means of local descriptors. The approach has advantages with complex image data like anatomical structures that exhibit high texture variation with limited relevance for the recognition of the object location. Experimental results and the comparison to AAMs on different data sets indicate that active feature models can improve search speed and result accuracy, considerably.
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Citations
Statistical shape models for 3D medical image segmentation: a review.
TL;DR: Statistical shape models (SSMs) have by now been firmly established as a robust tool for segmentation of medical images as discussed by the authors, primarily made possible by breakthroughs in automatic detection of shape correspondences.
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Boosted Regression Active Shape Models
David Cristinacce,Timothy F. Cootes +1 more
- 01 Sep 2007
TL;DR: It is shown that within the local iterative search of the ASM the local feature regression provides improved localisation on two publicly available human face test sets as well as increasing the search speed by a factor of eight.
Sparse MRF Appearance Models for Fast Anatomical Structure Localisation
René Donner,Branislav Micusik,Georg Langs,Horst Bischof +3 more
- 01 Jan 2007
TL;DR: This paper presents an approach that localises anatomical structures in a global manner by means of Markov Random Fields (MRF), which does not need initialisation, but finds the most plausible match of the query structure in the image.
Wavelet-driven knowledge-based MRI calf muscle segmentation
Salma Essafi,Georg Langs,J.-F. Deux,Alain Rahmouni,Guillaume Bassez,N. Paragios +5 more
- 28 Jun 2009
TL;DR: A novel representation of shape variation using diffusion wavelets, and a search paradigm based on local features that is independent from the topology of the anatomical structure, and can represent complex geometric and photometric dependencies of the structure of interest.
28
Generalized sparse MRF appearance models
TL;DR: This paper localizes anatomical structures in a global manner by formulating the localization task as the solution of a Markov Random Field (MRF) and finds the most plausible match of the query structure in the entire image.
22
References
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Active appearance models
Abstract: We describe a new method of matching statistical models of appearance to images. A set of model parameters control modes of shape and gray-level variation learned from a training set. We construct an efficient iterative matching algorithm by learning the relationship between perturbations in the model parameters and the induced image errors.