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» Adaptive object tracking by learning background context
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ICCV
2011
IEEE
13 years 9 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
ICPR
2006
IEEE
15 years 10 months ago
A Target Dependent Colorspace for Robust Tracking
The selection of the appropriate colorspace for tracking applications has not been an issue previously considered in the literature. Many color representations have been suggested...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
CVPR
2010
IEEE
15 years 5 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
101
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CVPR
2004
IEEE
15 years 11 months ago
An Unsupervised, Online Learning Framework for Moving Object Detection
Object detection with a learned classifier has been applied successfully to difficult tasks such as detecting faces and pedestrians. Systems using this approach usually learn the ...
Vinod Nair, James J. Clark
PAMI
2008
235views more  PAMI 2008»
14 years 9 months ago
Dependent Multiple Cue Integration for Robust Tracking
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and po...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...