Unsupervised construction of human body models
作者: Thomas WaltherRolf P. Würtz
作者单位: 1Department of Electrical Engineering and Information Technology and Institute for Neural Computation, Ruhr-University Bochum, Germany
刊名: Cognitive Systems Research, 2018, Vol.47 , pp.68-84
来源数据库: Elsevier Journal
DOI: 10.1016/j.cogsys.2017.08.001
关键词: Structure learningLearning a visual representationUpper body pose estimation
英文摘要: Abstract(#br)Unsupervised learning of a generalizable model of the visual appearance of humans from video data is of major importance for computing systems interacting naturally with their users and others. We propose a step towards automatic behavior understanding by making the posture estimation cycle more autonomous. The system extracts coherent motion from moving upper bodies and autonomously decides about limbs and their possible spatial relationships. The models from many videos are integrated into a meta-model, which shows good generalization with respect to different individuals, backgrounds, and attire. This model allows robust interpretation of single video frames without temporal continuity and posture mimicking by an android robot.
全文获取路径: Elsevier  (合作)
影响因子:0.75 (2012)

  • construction 构造
  • learning 学识
  • representation 表现
  • visual 可见
  • human 人的
  • estimation 估计
  • Upper 上方