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ISBI
2007
IEEE
13 years 11 months ago
Advanced Particle Filtering for Multiple Object Tracking in Dynamic Fluorescence Microscopy Images
Quantitative analysis of dynamical processes in living cells by means of fluorescence microscopy imaging requires tracking of hundreds of bright spots in noisy image sequences. D...
Ihor Smal, Wiro J. Niessen, Erik H. W. Meijering
ICCV
2007
IEEE
13 years 7 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
ECCV
2008
Springer
14 years 7 months ago
A Probabilistic Approach to Integrating Multiple Cues in Visual Tracking
Abstract. This paper presents a novel probabilistic approach to integrating multiple cues in visual tracking. We perform tracking in different cues by interacting processes. Each p...
Wei Du, Justus H. Piater
FGR
2004
IEEE
141views Biometrics» more  FGR 2004»
13 years 9 months ago
Smart Particle Filtering for 3D Hand Tracking
Solving the tracking of an articulated structure in a reasonable time is a complex task mainly due to the high dimensionality of the problem. A new optimization method, called Sto...
Matthieu Bray, Esther Koller-Meier, Luc J. Van Goo...
TIP
2010
141views more  TIP 2010»
13 years 1 days ago
Efficient Particle Filtering via Sparse Kernel Density Estimation
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
Amit Banerjee, Philippe Burlina