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» Metric clustering via consistent labeling
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PAMI
2011
12 years 11 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 6 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 2 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 6 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
13 years 11 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