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» Non-Parametric Probabilistic Image Segmentation
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NIPS
2001
13 years 9 months ago
Bayesian time series classification
This paper proposes an approach to classification of adjacent segments of a time series as being either of classes. We use a hierarchical model that consists of a feature extract...
Peter Sykacek, Stephen J. Roberts
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-...
TMM
2002
104views more  TMM 2002»
13 years 7 months ago
Spatial contextual classification and prediction models for mining geospatial data
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
CVPR
2011
IEEE
12 years 11 months ago
Connecting Non-Quadratic Variational Models and MRFs
Spatially-discrete Markov random fields (MRFs) and spatially-continuous variational approaches are ubiquitous in low-level vision, including image restoration, segmentation, opti...
Kevin Schelten, Stefan Roth
IBERAMIA
2010
Springer
13 years 6 months ago
Detection of Multiple People by a Mobile Robot in Dynamic Indoor Environments
Detection of multiple people is a key element for social robot design and it is a requirement for effective human-robot interaction. However, it is not an easy task, especially in...
José Alberto Méndez-Polanco, Ang&eac...