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» An optical flow probabilistic observation model for tracking
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SP
2010
IEEE
210views Security Privacy» more  SP 2010»
13 years 11 months ago
Reconciling Belief and Vulnerability in Information Flow
Abstract—Belief and vulnerability have been proposed recently to quantify information flow in security systems. Both concepts stand as alternatives to the traditional approaches...
Sardaouna Hamadou, Vladimiro Sassone, Catuscia Pal...
PAMI
2010
238views more  PAMI 2010»
13 years 6 months ago
Tracking Motion, Deformation, and Texture Using Conditionally Gaussian Processes
—We present a generative model and inference algorithm for 3D nonrigid object tracking. The model, which we call G-flow, enables the joint inference of 3D position, orientation, ...
Tim K. Marks, John R. Hershey, Javier R. Movellan
ISVC
2007
Springer
14 years 1 months ago
Blur in Human Vision and Increased Visual Realism in Virtual Environments
Abstract. A challenge for virtual reality (VR) applications is to increase the realism of an observer’s visual experience. For this purpose the variation of the blur an observer ...
Michael S. Bittermann, I. Sevil Sariyildiz, Ö...
ECCV
2004
Springer
14 years 9 months ago
Hand Motion from 3D Point Trajectories and a Smooth Surface Model
A method is proposed to track the full hand motion from 3D points reconstructed using a stereoscopic set of cameras. This approach combines the advantages of methods that use 2D mo...
Guillaume Dewaele, Frederic Devernay, Radu Horaud
ICPR
2008
IEEE
14 years 2 months ago
Tracking human body by using particle filter Gaussian process Markov-switching model
The goal of this article is to present an effective and robust tracking algorithm for nonlinear feet motion by deploying particle filter integrated with Gaussian process latent v...
Jing Wang, Hong Man, Yafeng Yin