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» A Discriminative Framework for Modelling Object Classes
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IROS
2007
IEEE
157views Robotics» more  IROS 2007»
14 years 3 months ago
A spatio-temporal probabilistic model for multi-sensor object recognition
— This paper presents a general framework for multi-sensor object recognition through a discriminative probabilistic approach modelling spatial and temporal correlations. The alg...
Bertrand Douillard, Dieter Fox, Fabio T. Ramos
CVPR
2010
IEEE
14 years 5 months ago
Multi-Class Object Localization by Combining Local Contextual Interactions
Recent work in object localization has shown that the use of contextual cues can greatly improve accuracy over models that use appearance features alone. Although many of these mo...
Carolina Galleguillos, Brian McFee, Gert Lanckriet
COLT
2006
Springer
14 years 25 days ago
Discriminative Learning Can Succeed Where Generative Learning Fails
Generative algorithms for learning classifiers use training data to separately estimate a probability model for each class. New items are classified by comparing their probabiliti...
Philip M. Long, Rocco A. Servedio
ICCV
2005
IEEE
14 years 11 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona
DAGM
2008
Springer
13 years 11 months ago
Sliding-Windows for Rapid Object Class Localization: A Parallel Technique
Abstract. This paper presents a fast object class localization framework implemented on a data parallel architecture currently available in recent computers. Our case study, the im...
Christian Wojek, Gyuri Dorkó, André ...