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SSIAI
2000
IEEE
13 years 11 months ago
A New Bayesian Relaxation Framework for the Estimation and Segmentation of Multiple Motions
In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
Alexander Strehl, Jake K. Aggarwal
ISBI
2007
IEEE
14 years 1 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
CVPR
2004
IEEE
14 years 9 months ago
A Probabilistic Framework for Combining Tracking Algorithms
For the past few years researches have been investigating enhancing tracking performance by combining several different tracking algorithms. We propose an analytically justified, ...
Ido Leichter, Michael Lindenbaum, Ehud Rivlin
CVPR
2010
IEEE
13 years 10 months ago
Real-time Tracking of Multiple Occluding Objects using Level Sets
We derive a probabilistic framework for robust, realtime, visual tracking of multiple previously unseen objects from a moving camera. This framework models the discrete depth orde...
Charles Bibby, Ian Reid
ATAL
2005
Springer
14 years 28 days ago
Real-time dense communication among agents for active tracking
For multi-target tracking, we realize the increase in number of simultaneously trackable objects and tracking stability by improving the way of communication proposed in [1] so th...
Norimichi Ukita