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» Semi-Supervised Learning of Mixture Models
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ICML
2005
IEEE
16 years 16 days ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
PR
2006
117views more  PR 2006»
14 years 11 months ago
On transforming statistical models for non-frontal face verification
: We address the pose mismatch problem which can occur in face verification systems that have only a single (frontal) face image available for training. In the framework of a Bayes...
Conrad Sanderson, Samy Bengio, Yongsheng Gao
PAMI
2006
138views more  PAMI 2006»
14 years 11 months ago
Context-Based Segmentation of Image Sequences
We describe an algorithm for context-based segmentation of visual data. New frames in an image sequence (video) are segmented based on the prior segmentation of earlier frames in ...
Jacob Goldberger, Hayit Greenspan
ECML
2001
Springer
15 years 4 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...
CVPR
2008
IEEE
16 years 1 months ago
Simultaneous clustering and tracking unknown number of objects
In this paper, we present a novel on-line probabilistic generative model that simultaneously deals with both the clustering and the tracking of an unknown number of moving objects...
Katsuhiko Ishiguro, Takeshi Yamada, Naonori Ueda