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» A Probabilistic Framework for Combining Tracking Algorithms
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PAMI
1998
112views more  PAMI 1998»
13 years 6 months ago
Efficient Region Tracking With Parametric Models of Geometry and Illumination
—As an object moves through the field of view of a camera, the images of the object may change dramatically. This is not simply due to the translation of the object across the im...
Gregory D. Hager, Peter N. Belhumeur
CLOR
2006
13 years 10 months ago
Sequential Learning of Layered Models from Video
Abstract. A popular framework for the interpretation of image sequences is the layers or sprite model, see e.g. [1], [2]. Jojic and Frey [3] provide a generative probabilistic mode...
Michalis K. Titsias, Christopher K. I. Williams
CVPR
2010
IEEE
14 years 2 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, ...
ILP
2000
Springer
13 years 10 months ago
Bayesian Logic Programs
First-order probabilistic models are recognized as efficient frameworks to represent several realworld problems: they combine the expressive power of first-order logic, which serv...
Kristian Kersting, Luc De Raedt
BMCBI
2006
126views more  BMCBI 2006»
13 years 6 months ago
A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data
Background: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heteroge...
Zizhen Yao, Walter L. Ruzzo