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» Tracking the Invisible: Learning Where the Object Might be
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PAMI
2007
118views more  PAMI 2007»
14 years 9 months ago
Learning to Transform Time Series with a Few Examples
We describe a semi-supervised regression algorithm that learns to transform one time series into another time series given examples of the transformation. This algorithm is applie...
Ali Rahimi, Ben Recht, Trevor Darrell
PAMI
2006
193views more  PAMI 2006»
14 years 9 months ago
A System for Learning Statistical Motion Patterns
Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, w...
Weiming Hu, Xuejuan Xiao, Zhouyu Fu, Dan Xie, Tien...
89
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ECCV
2008
Springer
15 years 11 months ago
Semi-supervised On-Line Boosting for Robust Tracking
Abstract. Recently, on-line adaptation of binary classifiers for tracking have been investigated. On-line learning allows for simple classifiers since only the current view of the ...
Helmut Grabner, Christian Leistner, Horst Bischof
CVPR
2005
IEEE
15 years 11 months ago
A Statistical Field Model for Pedestrian Detection
This paper presents a new statistical model for detecting and tracking deformable objects such as pedestrians, where large shape variations induced by local shape deformation can ...
Ying Wu, Ting Yu, Gang Hua
ICCV
2001
IEEE
15 years 11 months ago
Human Tracking with Mixtures of Trees
Tree-structured probabilistic models admit simple, fast inference. However, they are not well suited to phenomena such as occlusion, where multiple components of an object may dis...
Sergey Ioffe, David A. Forsyth