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» Variations on U-Shaped Learning
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CVPR
2008
IEEE
14 years 9 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
PAMI
2011
13 years 2 months ago
Learning a Family of Detectors via Multiplicative Kernels
—Object detection is challenging when the object class exhibits large within-class variations. In this work, we show that foreground-background classification (detection) and wit...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...
ICCV
2003
IEEE
14 years 9 months ago
Learning Pedestrian Models for Silhouette Refinement
We present a model-based method for accurate extraction of pedestrian silhouettes from video sequences. Our approach is based on two assumptions, 1) there is a common appearance t...
L. Lee, Gerald Dalley, Kinh Tieu
ECCV
2006
Springer
14 years 9 months ago
Globally Optimal Active Contours, Sequential Monte Carlo and On-Line Learning for Vessel Segmentation
In this paper we propose a Particle Filter-based propagation approach for the segmentation of vascular structures in 3D volumes. Because of pathologies and inhomogeneities, many de...
Charles Florin, Nikos Paragios, James Williams
ICCV
2009
IEEE
13 years 5 months ago
Real-time visual tracking via Incremental Covariance Tensor Learning
Visual tracking is a challenging problem, as an object may change its appearance due to pose variations, illumination changes, and occlusions. Many algorithms have been proposed t...
Yi Wu, Jian Cheng, Jinqiao Wang, Hanqing Lu