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» Computation with imprecise probabilities
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CVPR
2005
IEEE
16 years 6 months ago
Kernel-Based Bayesian Filtering for Object Tracking
Particle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, the algorithm is based on a Monte Ca...
Bohyung Han, Ying Zhu, Dorin Comaniciu, Larry S. D...
168
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ICCV
2003
IEEE
16 years 6 months ago
Graph Partition by Swendsen-Wang Cuts
Vision tasks, such as segmentation, grouping, recognition, can be formulated as graph partition problems. The recent literature witnessed two popular graph cut algorithms: the Ncu...
Adrian Barbu, Song Chun Zhu
ICCV
2001
IEEE
16 years 6 months ago
Joint Feature Distributions for Image Correspondence
We introduce `Joint Feature Distributions', a general statistical framework for feature based multi-image matching that explicitly models the joint probability distributions ...
Bill Triggs
ICIP
2001
IEEE
16 years 6 months ago
A comparison of discrete and continuous output modeling techniques for a pseudo-2D hidden Markov model face recognition system
Face recognition has become an important topic within the field of pattern recognition and computer vision. In this field a number of different approaches to feature extraction, m...
Frank Wallhoff, Stefan Eickeler, Gerhard Rigoll
ICPR
2006
IEEE
16 years 5 months ago
Boosted Markov Chain Monte Carlo Data Association for Multiple Target Detection and Tracking
In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as ...
Bo Wu, Gérard G. Medioni, Isaac Cohen, Qian...