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» A Probabilistic Framework for Combining Tracking Algorithms
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148
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ICCV
2007
IEEE
15 years 4 months ago
Probabilistic Fusion Tracking Using Mixture Kernel-Based Bayesian Filtering
Even though sensor fusion techniques based on particle filters have been applied to object tracking, their implementations have been limited to combining measurements from multip...
Bohyung Han, Seong-Wook Joo, Larry S. Davis
117
Voted
EMNLP
2007
15 years 4 months ago
Dependency Parsing and Domain Adaptation with LR Models and Parser Ensembles
We present a data-driven variant of the LR algorithm for dependency parsing, and extend it with a best-first search for probabilistic generalized LR dependency parsing. Parser act...
Kenji Sagae, Jun-ichi Tsujii
113
Voted
ICPR
2004
IEEE
16 years 3 months ago
Probabilistic Object Tracking Using Multiple Features
We present a generic tracker which can handle a variety of different objects. For this purpose, groups of low-level features like interest points, edges, homogeneous and textured ...
David Serby, Esther Koller-Meier, Luc J. Van Gool
DAGM
2001
Springer
15 years 7 months ago
A Probabilistic Approach to Simultaneous Segmentation, Object Recognition, 3D Localization, and Tracking Using Stereo
Vision systems for service robotics applications have to cope with varying environmental conditions, partial occlusions, complex backgrounds and a large number of distractors (clut...
Georg von Wichert
94
Voted
UAI
1996
15 years 3 months ago
Bucket elimination: A unifying framework for probabilistic inference
Probabilistic inference algorithms for belief updating, nding the most probable explanation, the maximum a posteriori hypothesis, and the maximum expected utility are reformulated...
Rina Dechter