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» Probabilistic Object Tracking Using Multiple Features
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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
ECCV
2002
Springer
14 years 9 months ago
Color-Based Probabilistic Tracking
Color-based trackers recently proposed in [3,4,5] have been proved robust and versatile for a modest computational cost. They are especially appealing for tracking tasks where the ...
Carine Hue, Jaco Vermaak, Michel Gangnet, Patrick ...
PAMI
2008
235views more  PAMI 2008»
13 years 7 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...
IROS
2007
IEEE
162views Robotics» more  IROS 2007»
14 years 1 months ago
Where is your dive buddy: tracking humans underwater using spatio-temporal features
— We present an algorithm for underwater robots to track mobile targets, and specifically human divers, by detecting periodic motion. Periodic motion is typically associated wit...
Junaed Sattar, Gregory Dudek
CVPR
2010
IEEE
13 years 7 months ago
A probabilistic framework for joint segmentation and tracking
Most tracking algorithms implicitly apply a coarse segmentation of each target object using a simple mask such as a rectangle or an ellipse. Although convenient, such coarse segme...
Chad Aeschliman, Johnny Park, Avinash C. Kak