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» Feature-aided particle tracking
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CEC
2007
IEEE
15 years 6 months ago
On performance metrics and particle swarm methods for dynamic multiobjective optimization problems
— This paper describes two performance measures for measuring an EMO (Evolutionary Multiobjective Optimization) algorithm’s ability to track a time-varying Paretofront in a dyn...
Xiaodong Li, Jürgen Branke, Michael Kirley
IROS
2009
IEEE
147views Robotics» more  IROS 2009»
15 years 6 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
88
Voted
ICCV
2009
IEEE
1265views Computer Vision» more  ICCV 2009»
16 years 4 months ago
Reconstructing 3D motion trajectories of particle swarms by global correspondence selection
This paper addresses the problem of reconstructing the 3D motion trajectories of particle swarms using two temporally synchronized and geometrically calibrated cameras. The 3D traj...
Danping Zou, Qi Zhao, Hai Shan Wu, Yan Qiu Chen
IROS
2006
IEEE
145views Robotics» more  IROS 2006»
15 years 6 months ago
Panoramic Vision and Laser Range Finder Fusion for Multiple Person Tracking
– This paper describes a fusion of panoramic vision and laser range data to track multiple persons simultaneously from a stationary robot. Particle filters are used to track peop...
Punarjay Chakravarty, Ray Jarvis
IVC
2007
89views more  IVC 2007»
14 years 11 months ago
Sequential Monte Carlo tracking by fusing multiple cues in video sequences
This paper presents visual cues for object tracking in video sequences using particle filtering. A consistent histogram-based framework is developed for the analysis of colour, e...
Paul Brasnett, Lyudmila Mihaylova, David R. Bull, ...