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ICCV
2007
IEEE
16 years 8 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...
ISBI
2008
IEEE
16 years 7 months ago
Segmentation of 4D MR renography images using temporal dynamics in a level set framework
A novel 4D level set framework was developed to segment dynamic MR images into the cortex, medulla and collecting system. The novelty of the method is that it combines information...
Ting Song, Vivian S. Lee, Henry Rusinek, Qun Chen,...
UAI
1998
15 years 8 months ago
Learning the Structure of Dynamic Probabilistic Networks
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
SIAMAM
2008
91views more  SIAMAM 2008»
15 years 6 months ago
A Fluid Dynamic Model for Telecommunication Networks with Sources and Destinations
This paper proposes a macroscopic fluid dynamic model dealing with the flows of information on a telecommunication network with sources and destinations. The model consists of a co...
Ciro D'Apice, Rosanna Manzo, Benedetto Piccoli
ISBI
2006
IEEE
16 years 7 months ago
Automated tracking and modeling of microtubule dynamics
The method of microtubule tracking and dynamics analysis, presented here, improves upon the current means of manual and automated quantification of microtubule behavior. Key contr...
Motaz A. El Saban, Alphan Altinok, Austin J. Peck,...