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» Robust Incremental Subspace Learning for Object Tracking
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ICASSP
2011
IEEE
12 years 11 months ago
Adaptive appearance learning for visual object tracking
This paper addresses online learning of reference object distribution in the context of two hybrid tracking schemes that combine the mean shift with local point feature correspond...
Zulfiqar Hassan Khan, Irene Yu-Hua Gu
WACV
2005
IEEE
14 years 1 months ago
Learning to Track Objects Through Unobserved Regions
As tracking systems become more effective at reliably tracking multiple objects over extended periods of time within single camera views and across overlapping camera views, incre...
Chris Stauffer
PREMI
2007
Springer
14 years 1 months ago
An Adaptive Bayesian Technique for Tracking Multiple Objects
Abstract. Robust tracking of objects in video is a key challenge in computer vision with applications in automated surveillance, video indexing, human-computer-interaction, gesture...
Pankaj Kumar, Michael J. Brooks, Anton van den Hen...
KDD
2008
ACM
119views Data Mining» more  KDD 2008»
14 years 7 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
ACCV
2006
Springer
14 years 1 months ago
Multiregion Level Set Tracking with Transformation Invariant Shape Priors
Tracking of regions and object boundaries in an image sequence is a well studied problem in image processing and computer vision. So far, numerous approaches tracking different fea...
Michael Fussenegger, Rachid Deriche, Axel Pinz