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Multiple Human Pose Estimation with Temporally Consistent 3D Pictorial Structures

  • Vasileios BelagiannisEmail author
  • Xinchao Wang
  • Bernt Schiele
  • Pascal Fua
  • Slobodan Ilic
  • Nassir Navab
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8925)

Abstract

Multiple human 3D pose estimation from multiple camera views is a challenging task in unconstrained environments. Each individual has to be matched across each view and then the body pose has to be estimated. Additionally, the body pose of every individual changes in a consistent manner over time. To address these challenges, we propose a temporally consistent 3D Pictorial Structures model (3DPS) for multiple human pose estimation from multiple camera views. Our model builds on the 3D Pictorial Structures to introduce the notion of temporal consistency between the inferred body poses. We derive this property by relying on multi-view human tracking. Identifying each individual before inference significantly reduces the size of the state space and positively influences the performance as well. To evaluate our method, we use two challenging multiple human datasets in unconstrained environments. We compare our method with the state-of-the-art approaches and achieve better results.

Keywords

Human pose estimation 3D pictorial structures Part-based pose estimation 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Vasileios Belagiannis
    • 1
    Email author
  • Xinchao Wang
    • 2
  • Bernt Schiele
    • 3
  • Pascal Fua
    • 2
  • Slobodan Ilic
    • 1
    • 4
  • Nassir Navab
    • 1
    • 5
  1. 1.Computer Aided Medical ProceduresTechnische Universität MünchenMünchenGermany
  2. 2. Computer Vision LaboratoryEPFLLausanneSwitzerland
  3. 3.Max Planck Institute for InformaticsSaarbrückenGermany
  4. 4.Siemens AGMunichGermany
  5. 5.Computer Aided Medical ProceduresJohns Hopkins UniversityBaltimoreUSA

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