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» A Bayesian Framework for Multi-cue 3D Object Tracking
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CRV
2009
IEEE
217views Robotics» more  CRV 2009»
13 years 11 months ago
Probabilistic 3D Tracking: Rollator Users' Leg Pose from Coronal Images
Understanding the human gait is an important objective towards improving elderly mobility. In turn, gait analyses largely depend on kinematic and dynamic measurements. While the m...
Samantha Ng, Adel H. Fakih, Adam Fourney, Pascal P...
ICIP
2003
IEEE
14 years 6 months ago
Real-time head tracking and 3D pose estimation from range data
In this paper a head tracking algorithm using 3D data is described. The system relies on a novel 3D sensor that generates a dense range image of the scene. By not relying on brigh...
Sotiris Malassiotis, Michael G. Strintzis
IJCV
2000
164views more  IJCV 2000»
13 years 4 months ago
Probabilistic Modeling and Recognition of 3-D Objects
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
Joachim Hornegger, Heinrich Niemann
BMVC
2010
13 years 2 months ago
Active 3D Segmentation through Fixation of Previously Unseen Objects
We present an approach for active segmentation based on integration of several cues. It serves as a framework for generation of object hypotheses of previously unseen objects in n...
Mårten Björkman, Danica Kragic
ICPR
2008
IEEE
13 years 11 months ago
2D and 3D upper body tracking with one framework
We propose a Dynamic Bayesian Network (DBN) model for upper body tracking. We first construct a Bayesian Network (BN) to represent the human upper body structure and then incorpo...
Lei Zhang, Jixu Chen, Zhi Zeng, Qiang Ji