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» Metric clustering via consistent labeling
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PAMI
2011
13 years 3 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang
IJCAI
2001
13 years 10 months ago
Probabilistic Classification and Clustering in Relational Data
Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...
Benjamin Taskar, Eran Segal, Daphne Koller
BMVC
2010
13 years 6 months ago
Live Feature Clustering in Video Using Appearance and 3D Geometry
We present a method for live grouping of feature points into persistent 3D clusters as a single camera browses a static scene, with no additional assumptions, training or infrastr...
Adrien Angeli, Andrew Davison
CVPR
2007
IEEE
14 years 10 months ago
Robust Estimation of Texture Flow via Dense Feature Sampling
Texture flow estimation is a valuable step in a variety of vision related tasks, including texture analysis, image segmentation, shape-from-texture and texture remapping. This pap...
Yu-Wing Tai, Michael S. Brown, Chi-Keung Tang
CVPR
2009
IEEE
14 years 3 months ago
Trajectory parsing by cluster sampling in spatio-temporal graph
The objective of this paper is to parse object trajectories in surveillance video against occlusion, interruption, and background clutter. We present a spatio-temporal graph (ST-G...
Xiaobai Liu, Liang Lin, Song Chun Zhu, Hai Jin