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» Robust Incremental Subspace Learning for Object Tracking
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105
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CVPR
2005
IEEE
15 years 8 months ago
Hand Tracking with Flocks of Features
This paper introduces “Flocks of Features,” a fast tracking method for non-rigid and highly articulated objects such as hands. It combines KLT features and a learned foregroun...
Mathias Kölsch, Matthew Turk
145
Voted
CVPR
2010
IEEE
15 years 10 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, ...
163
Voted
WACV
2012
IEEE
13 years 10 months ago
Online discriminative object tracking with local sparse representation
We propose an online algorithm based on local sparse representation for robust object tracking. Local image patches of a target object are represented by their sparse codes with a...
Qing Wang, Feng Chen, Wenli Xu, Ming-Hsuan Yang
119
Voted
ICCV
2011
IEEE
14 years 2 months ago
Hough-based Tracking of Non-Rigid Objects
Online learning has shown to be successful in tracking of previously unknown objects. However, most approaches are limited to a bounding-box representation with fixed aspect rati...
Martin Godec, Peter M. Roth, Horst Bischof
118
Voted
PAMI
2000
113views more  PAMI 2000»
15 years 2 months ago
Hierarchical Discriminant Regression
This paper presents a new technique which incrementally builds a hierarchical discriminant regression (IHDR) tree for generation of motion based robot reactions. The robot learned...
Wey-Shiuan Hwang, Juyang Weng