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ACL
2012
11 years 7 months ago
Using Rejuvenation to Improve Particle Filtering for Bayesian Word Segmentation
We present a novel extension to a recently proposed incremental learning algorithm for the word segmentation problem originally introduced in Goldwater (2006). By adding rejuvenat...
Benjamin Börschinger, Mark Johnson
CVPR
2004
IEEE
14 years 6 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
IPMI
2007
Springer
14 years 5 months ago
Rao-Blackwellized Marginal Particle Filtering for Multiple Object Tracking in Molecular Bioimaging
Modern live cell fluorescence microscopy imaging systems, used abundantly for studying intra-cellular processes in vivo, generate vast amounts of noisy image data that cannot be pr...
Ihor Smal, Katharina Draegestein, Niels Galjart, W...
PAMI
2008
235views more  PAMI 2008»
13 years 4 months ago
Dependent Multiple Cue Integration for Robust Tracking
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and po...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
EMMCVPR
2011
Springer
12 years 4 months ago
Data-Driven Importance Distributions for Articulated Tracking
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...
Søren Hauberg, Kim Steenstrup Pedersen