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» Adaptive object tracking by learning background context
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CVPR
2009
IEEE
1413views Computer Vision» more  CVPR 2009»
16 years 4 months ago
Learning Semantic Scene Models by Object Classification and Trajectory Clustering
The visual surveillance task is to monitor the activity of objects in a scene. In far-field settings (i.e., wide outdoor areas), the majority of visible activities are objects movi...
Hanqing Lu, Stan Z. Li, Tianzhu Zhang
80
Voted
ICWS
2007
IEEE
14 years 11 months ago
A Semantic Web Services-based Infrastructure for Context-Adaptive Process Support
Current technologies aimed at supporting processes – whether it is a business or learning process – primarily follow a metadata- and data-centric paradigm. Whereas process met...
Stefan Dietze, Alessio Gugliotta, John Domingue
ICCV
2001
IEEE
15 years 11 months ago
BraMBLe: A Bayesian Multiple-Blob Tracker
Blob trackers have become increasingly powerful in recent years largely due to the adoption of statistical appearance models which allow effective background subtraction and robus...
Michael Isard, John MacCormick
ECCV
2008
Springer
15 years 11 months ago
Online Tracking and Reacquisition Using Co-trained Generative and Discriminative Trackers
Visual tracking is a challenging problem, as an object may change its appearance due to viewpoint variations, illumination changes, and occlusion. Also, an object may leave the fie...
Gérard G. Medioni, Qian Yu, Thang Ba Dinh
CRV
2011
IEEE
305views Robotics» more  CRV 2011»
13 years 9 months ago
Motion Segmentation by Learning Homography Matrices from Motor Signals
—Motion information is an important cue for a robot to separate foreground moving objects from the static background world. Based on the observation that the motion of the backgr...
Changhai Xu, Jingen Liu, Benjamin Kuipers