Loose-limbed people: estimating 3D human pose and motion using non-parametric belief propagation

DOI10.1007/s11263-011-0493-4zbMath1254.68283OpenAlexW2071882725MaRDI QIDQ1931578

Horst Haussecker, Michael J. Black, Michael Isard, Leonid Sigal

Publication date: 15 January 2013

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

Full work available at URL: https://doi.org/10.1007/s11263-011-0493-4

zbMATH Keywords

articulated trackinghuman motion trackinghuman pose estimationarticulated pose estimationnon-parametric belief propagation

Mathematics Subject Classification ID

Machine vision and scene understanding (68T45)

Related Items (3)

3D human pose tracking priors using geodesic mixture models ⋮ A Bayesian approach to multi-view 4D modeling ⋮ Dynamic and robust Bayesian graphical models

Uses Software

• OpenCV
• HumanEva

Cites Work

• Learning the statistics of people in images and video
• The computational complexity of probabilistic inference using Bayesian belief networks
• Sequential Monte Carlo Methods in Practice
• Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology
• The Visual Analysis of Human Movement: A Survey
• A Survey of Computer Vision-Based Human Motion Capture
• Probabilistic methods for finding people
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