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» Selectivity Estimation using Probabilistic Models
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CVPR
2008
IEEE
16 years 7 months ago
Scale invariance without scale selection
In this work we construct scale invariant descriptors (SIDs) without requiring the estimation of image scale; we thereby avoid scale selection which is often unreliable. Our start...
Iasonas Kokkinos, Alan L. Yuille
EMMCVPR
2001
Springer
15 years 9 months ago
Designing the Minimal Structure of Hidden Markov Model by Bisimulation
Hidden Markov Models (HMMs) are an useful and widely utilized approach to the modeling of data sequences. One of the problems related to this technique is finding the optimal stru...
Manuele Bicego, Agostino Dovier, Vittorio Murino
CVPR
2009
IEEE
2358views Computer Vision» more  CVPR 2009»
17 years 6 days ago
Pictorial Structures Revisited: People Detection and Articulated Pose Estimation
Non-rigid object detection and articulated pose estimation are two related and challenging problems in computer vision. Numerous models have been proposed over the years and oft...
Mykhaylo Andriluka (TU Darmstadt), Stefan Roth (TU...
JISE
2010
144views more  JISE 2010»
14 years 11 months ago
Variant Methods of Reduced Set Selection for Reduced Support Vector Machines
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
Li-Jen Chien, Chien-Chung Chang, Yuh-Jye Lee
ICCV
2007
IEEE
16 years 6 months ago
Object Localisation Using Generative Probability Model for Spatial Constellation and Local Image Features
In this paper we apply state-of-the-art approach to object detection and localisation by incorporating local descriptors and their spatial configuration into a generative probabil...
Joni-Kristian Kamarainen, Miroslav Hamouz, Josef K...