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» Gaussian Process Dynamical Models for Human Motion
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CVPR
2006
IEEE
15 years 5 months ago
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
CVPR
2003
IEEE
16 years 1 months ago
Shape-From-Silhouette of Articulated Objects and its Use for Human Body Kinematics Estimation and Motion Capture
Shape-From-Silhouette (SFS), also known as Visual Hull (VH) construction, is a popular 3D reconstruction method which estimates the shape of an object from multiple silhouette ima...
German K. M. Cheung, Simon Baker, Takeo Kanade
PR
2007
107views more  PR 2007»
14 years 11 months ago
Newtonian clustering: An approach based on molecular dynamics and global optimization
Given a data set, a dynamical procedure is applied to the data points in order to shrink and separate, possibly overlapping clusters. Namely, Newton’s equations of motion are em...
Konstantinos Blekas, Isaac E. Lagaris
ICPR
2010
IEEE
14 years 9 months ago
Information Theoretic Expectation Maximization Based Gaussian Mixture Modeling for Speaker Verification
The expectation maximization (EM) algorithm is widely used in the Gaussian mixture model (GMM) as the state-of-art statistical modeling technique. Like the classical EM method, th...
Sheeraz Memon, Margaret Lech, Namunu Chinthaka Mad...
ICIP
2005
IEEE
15 years 5 months ago
Silhouette-based probabilistic 2D human motion estimation for real-time applications
This paper presents a novel technique for 2D human motion estimation using a single non calibrated camera. The user’s five crucial human features (head, hands and feet) are ext...
Pedro Correa, Jacek Czyz, Toshiyuki Umeda, Ferran ...