Predicting articulated human motion from spatial processes

DOI10.1007/s11263-011-0433-3zbMath1235.68267OpenAlexW1994499467WikidataQ28477799 ScholiaQ28477799MaRDI QIDQ409100

Kim Steenstrup Pedersen, Søren Hauberg

Publication date: 12 April 2012

Published in: International Journal of Computer Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11263-011-0433-3

zbMATH Keywords

predictioninverse kinematicsparticle filteringmotion analysisarticulated human motionarticulated tracking

Mathematics Subject Classification ID

Machine vision and scene understanding (68T45)

Related Items (3)

Unscented Kalman filtering on Riemannian manifolds ⋮ Combinatorial resampling particle filter: an effective and efficient method for articulated object tracking ⋮ Sub-sample swapping for sequential Monte Carlo approximation of high-dimensional densities in the context of complex object tracking

Uses Software

• PRMLT

Cites Work

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• Numerical Optimization
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• Computer Vision - ECCV 2004

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