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HUMO
2007
Springer
13 years 11 months ago
Modeling Human Locomotion with Topologically Constrained Latent Variable Models
Abstract. Learned, activity-specific motion models are useful for human pose and motion estimation. Nevertheless, while the use of activityspecific models simplifies monocular t...
Raquel Urtasun, David J. Fleet, Neil D. Lawrence
ICCV
2007
IEEE
14 years 7 months ago
Real-time Body Tracking Using a Gaussian Process Latent Variable Model
In this paper, we present a tracking framework for capturing articulated human motions in real-time, without the need for attaching markers onto the subject's body. This is a...
Shaobo Hou, Aphrodite Galata, Fabrice Caillette, N...
ICCV
2009
IEEE
13 years 3 months ago
Complex volume and pose tracking with probabilistic dynamical models and visual hull constraints
We propose a method for estimating the pose of a human body using its approximate 3D volume (visual hull) obtained in real time from synchronized videos. Our method can cope with ...
Norimichi Ukita, Michiro Hirai, Masatsugu Kidode
IBPRIA
2005
Springer
13 years 11 months ago
A 3D Dynamic Model of Human Actions for Probabilistic Image Tracking
Abstract. In this paper we present a method suitable to be used for human tracking as a temporal prior in a particle filtering framework such as CONDENSATION [5]. This method is f...
Ignasi Rius, Daniel Rowe, Jordi Gonzàlez, F...
CVPR
2006
IEEE
14 years 7 months ago
3D People Tracking with Gaussian Process Dynamical Models
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
Raquel Urtasun, David J. Fleet, Pascal Fua