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» Pruning Training Sets for Learning of Object Categories
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CVPR
2008
IEEE
14 years 11 months ago
Sparse probabilistic regression for activity-independent human pose inference
Discriminative approaches to human pose inference involve mapping visual observations to articulated body configurations. Current probabilistic approaches to learn this mapping ha...
Raquel Urtasun, Trevor Darrell
ICASSP
2010
IEEE
13 years 9 months ago
Multi-View Object Detection by Classifier Interpolation
In this paper, we propose a novel solution for multi-view object detection. Given a set of training examples at different views, we select examples at a few key views and train on...
Xiaobai Liu, Haifeng Gong, Shuicheng Yan, Hai Jin
CVPR
2008
IEEE
14 years 11 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
IROS
2009
IEEE
198views Robotics» more  IROS 2009»
14 years 3 months ago
Scalable learning for object detection with GPU hardware
Abstract— We consider the problem of robotic object detection of such objects as mugs, cups, and staplers in indoor environments. While object detection has made significant pro...
Adam Coates, Paul Baumstarck, Quoc V. Le, Andrew Y...
ICCV
2005
IEEE
14 years 2 months ago
Object Categorization by Learned Universal Visual Dictionary
This paper presents a new algorithm for the automatic recognition of object classes from images (categorization). Compact and yet discriminative appearance-based object class mode...
John M. Winn, Antonio Criminisi, Thomas P. Minka