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CVPR
1999
IEEE
1071views Computer Vision» more  CVPR 1999»
16 years 3 months ago
Adaptive Background Mixture Models for Real-Time Tracking
A common method for real-time segmentation of moving regions in image sequences involves "background subtraction," or thresholding the error between an estimate of the i...
Chris Stauffer, W. Eric L. Grimson
92
Voted
ICCV
2005
IEEE
15 years 7 months ago
Priors for People Tracking from Small Training Sets
We advocate the use of Scaled Gaussian Process Latent Variable Models (SGPLVM) to learn prior models of 3D human pose for 3D people tracking. The SGPLVM simultaneously optimizes a...
Raquel Urtasun, David J. Fleet, Aaron Hertzmann, P...
152
Voted
CVPR
2008
IEEE
16 years 3 months ago
Context and observation driven latent variable model for human pose estimation
Current approaches to pose estimation and tracking can be classified into two categories: generative and discriminative. While generative approaches can accurately determine human...
Abhinav Gupta, Trista Chen, Francine Chen, Don Kim...
117
Voted
BMVC
2001
15 years 4 months ago
A SOM Based Approach to Skin Detection with Application in Real Time Systems
A large body of human image processing techniques use skin detection as a first primitive for subsequent feature extraction. Well established methods of colour modelling, such as...
David A. Brown, Ian Craw, Julian Lewthwaite
PAMI
2008
182views more  PAMI 2008»
15 years 1 months ago
Gaussian Process Dynamical Models for Human Motion
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
Jack M. Wang, David J. Fleet, Aaron Hertzmann