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CVPR
2009
IEEE
15 years 2 months ago
Learning to Track with Multiple Observers
We propose a novel approach to designing algorithms for object tracking based on fusing multiple observation models. As the space of possible observation models is too large for...
Björn Stenger, Roberto Cipolla, Thomas Woodle...
CVPR
2007
IEEE
14 years 9 months ago
Online Spatial-temporal Data Fusion for Robust Adaptive Tracking
One problem with the adaptive tracking is that the data that are used to train the new target model often contain errors and these errors will affect the quality of the new target...
Jixu Chen, Qiang Ji
ISBI
2007
IEEE
14 years 2 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
ICRA
2009
IEEE
175views Robotics» more  ICRA 2009»
13 years 5 months ago
A combination of particle filtering and deterministic approaches for multiple kernel tracking
Color-based tracking methods have proved to be efficient for their robustness qualities. The drawback of such global representation of an object is the lack of information on its s...
Céline Teuliere, Éric Marchand, Laur...
ETRA
2006
ACM
143views Biometrics» more  ETRA 2006»
14 years 1 months ago
openEyes: a low-cost head-mounted eye-tracking solution
Eye tracking has long held the promise of being a useful methodology for human computer interaction. However, a number of barriers have stood in the way of the integration of eye ...
Dongheng Li, Jason S. Babcock, Derrick Parkhurst