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» A Probabilistic Framework for Combining Tracking Algorithms
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ICIP
2005
IEEE
14 years 9 months ago
Tracking multiple cells by correspondence resolution in a sequential Bayesian framework
We propose a multi-target tracking (MTT) algorithm in a sequential Bayesian framework that computes cell velocities from video microscopy. Unlike the traditional tracking methods,...
Nilanjan Ray, Gang Dong, Scott T. Acton
ICPR
2002
IEEE
14 years 8 months ago
Tracking People
This paper describes a real-time computer vision system for tracking people in monocular video sequences. The system tracks people as they move through the camera's field of ...
Ng Kim Piau, Surendra Ranganath
CLEAR
2006
Springer
116views Biometrics» more  CLEAR 2006»
13 years 11 months ago
Multi-and Single View Multiperson Tracking for Smart Room Environments
Abstract. Simultaneous tracking of multiple persons in real world environments is an active research field and several approaches have been proposed, based on a variety of features...
Keni Bernardin, Tobias Gehrig, Rainer Stiefelhagen
ECCV
2008
Springer
14 years 9 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
IROS
2009
IEEE
147views Robotics» more  IROS 2009»
14 years 2 months ago
Vision-based estimation of three-dimensional position and pose of multiple underwater vehicles
— This paper describes a model-based probabilistic framework for tracking a fleet of laboratory-scale underwater vehicles using multiple fixed cameras. We model the target moti...
Sachit Butail, Derek A. Paley