Article

Human pose estimation from monocular image captures

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Wen-Nung LieAuthors Info & Claims

ICME'09: Proceedings of the 2009 IEEE international conference on Multimedia and Expo

Pages 994 - 997

Published: 28 June 2009 Publication History

Abstract

A human pose estimation method from monocular image captures is presented. The objective is to develop a human-computer interface (HCI) for virtual sport activities. In the proposed technique, a graphical 3D human model is first constructed. Its projection on a virtual image plane is then used to match the silhouettes obtained from the image sequence. By iteratively adjusting the 3D pose of the graphical 3D model with the physical and anatomic constraints of human motion, the human pose and the associate 3D motion parameters can be uniquely identified. Experimental results are presented with the real scene images.

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HuaWei PChao AChunMing GLiu ZJorge JPan ZZhang XAu ODong W(2011)A new approach for body pose recoveryProceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry10.1145/2087756.2087791(243-248)Online publication date: 11-Dec-2011
https://dl.acm.org/doi/10.1145/2087756.2087791

Human pose estimation from monocular image captures
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
  2. Computer graphics
    1. Animation

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ICME'09: Proceedings of the 2009 IEEE international conference on Multimedia and Expo

June 2009

1844 pages

ISBN:9781424442904

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IEEE Press

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Published: 28 June 2009

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HuaWei PChao AChunMing GLiu ZJorge JPan ZZhang XAu ODong W(2011)A new approach for body pose recoveryProceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry10.1145/2087756.2087791(243-248)Online publication date: 11-Dec-2011
https://dl.acm.org/doi/10.1145/2087756.2087791

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Human Pose Estimation from Monocular Videos

Monocular human pose estimation: A survey of deep learning-based methods

Model-based human pose estimation and tracking

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