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ECML
2001
Springer
13 years 12 months ago
Learning of Variability for Invariant Statistical Pattern Recognition
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciï...
Daniel Keysers, Wolfgang Macherey, Jörg Dahme...
ICIP
2005
IEEE
14 years 9 months ago
A probabilistic model for robust face alignment in videos
A new approach for localizing facial structure in videos is proposed in this paper by modeling shape alignment dynamically. The approach makes use of the spatial-temporal continuit...
Wei Zhang, Yi Zhou, Xiaoou Tang, Junhui Deng
IJCV
2007
146views more  IJCV 2007»
13 years 7 months ago
Statistical Multi-Object Shape Models
The shape of a population of geometric entities is characterized by both the common geometry of the population and the variability among instances. In the deformable model approach...
Conglin Lu, Stephen M. Pizer, Sarang C. Joshi, Ja-...
MICCAI
2007
Springer
14 years 8 months ago
Shape Analysis Using a Point-Based Statistical Shape Model Built on Correspondence Probabilities
A fundamental problem when computing statistical shape models is the determination of correspondences between the instances of the associated data set. Often, homologies between po...
Heike Hufnagel, Xavier Pennec, Jan Ehrhardt, Heinz...
BIB
2006
141views more  BIB 2006»
13 years 7 months ago
Statistical significance in biological sequence analysis
One of the major goals of computational sequence analysis is to find sequence similarities, which could serve as evidence of structural and functional conservation, as well as of ...
Alexander Yu. Mitrophanov, Mark Borodovsky