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» A Probabilistic Background Model for Tracking
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ICPR
2006
IEEE
16 years 28 days ago
Part-Based Probabilistic Point Matching
Correspondence algorithms typically struggle with shapes that display part-based variation. We present a probabilistic approach that matches shapes using independent part transfor...
Graham McNeill, Sethu Vijayakumar
TASLP
2010
109views more  TASLP 2010»
14 years 6 months ago
Multipitch Estimation of Piano Sounds Using a New Probabilistic Spectral Smoothness Principle
Abstract--A new method for the estimation of multiple concurrent pitches in piano recordings is presented. It addresses the issue of overlapping overtones by modeling the spectral ...
Valentin Emiya, Roland Badeau, Bertrand David
ICCV
2005
IEEE
15 years 5 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...
IVC
2006
154views more  IVC 2006»
14 years 11 months ago
Manifold based analysis of facial expression
We propose a novel approach for modeling, tracking and recognizing facial expressions. Our method works on a low dimensional expression manifold, which is obtained by Isomap embed...
Ya Chang, Changbo Hu, Rogerio Feris, Matthew Turk
ICRA
2010
IEEE
170views Robotics» more  ICRA 2010»
14 years 10 months ago
Dynamic 3D scene analysis for acquiring articulated scene models
— In this paper we present a new system for a mobile robot to generate an articulated scene model by analyzing complex dynamic 3D scenes. The system extracts essential knowledge ...
Agnes Swadzba, Niklas Beuter, Sven Wachsmuth, Fran...