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» A Bayesian Framework for Multi-cue 3D Object Tracking
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ICMCS
2006
IEEE
234views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Decentralized Multiple Camera Multiple Object Tracking
In this paper, we present a novel decentralized Bayesian framework using multiple collaborative cameras for robust and efficient multiple object tracking with significant and pe...
Wei Qu, Dan Schonfeld, Magdi A. Mohamed
ICIP
2005
IEEE
14 years 9 months ago
Joint feature-spatial-measure space: a new approach to highly efficient probabilistic object tracking
In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Feng Chen, XiaoTong Yuan, ShuTang Yang
CVPR
2000
IEEE
14 years 9 months ago
Real-Time Tracking of Non-Rigid Objects Using Mean Shift
A new method for real-time tracking of non-rigid objects seen from a moving camera is proposed. The central computational module is based on the mean shift iterations and nds the ...
Dorin Comaniciu, Visvanathan Ramesh, Peter Meer
IJRR
2007
218views more  IJRR 2007»
13 years 7 months ago
Real-time Hybrid Tracking using Edge and Texture Information
This paper proposes a real-time, robust and effective tracking framework for visual servoing applications. The algorithm is based on the fusion of visual cues and on the estimatio...
Muriel Pressigout, Éric Marchand
ICIP
2009
IEEE
14 years 8 months ago
Semantic Labeling Of Track Events Using Time Series Segmentation And Shape Analysis
This paper presents a novel framework for applying semantic labels to events within a track. A track is a two-dimensional (2D) or a three-dimensional (3D) signal in time where eac...