Recent Developments on 2D Pose Estimation From Monocular Images

  • Artur Bąk
  • Marek Kulbacki
  • Jakub Segen
  • Dawid Świątkowski
  • Kamil Wereszczyński
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9622)

Abstract

Human pose estimation from monocular images is one of the most significant aspects of modern computer vision tasks and its application demand is still increasing in such areas as automatic images indexing or human activity recognition from video. Among many approaches applied in these areas the one based on pose estimation gives, beyond all doubts, one of the most powerful representation of human on the picture in sense of sparsity and semantics. In this paper we provide a detailed survey of the most efficient methods in 2D pose estimation domain as well as the test results of selected methods on the LSP dataset, which is commonly used by state-of-the-art works.

Keywords

Human pose estimation PSM Poselet 
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Notes

Acknowledgements

This work has been supported by the National Centre for Research and Development (project UOD-DEM-1-183/001 “Intelligent video analysis system for behavior and event recognition in surveillance networks”).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Artur Bąk
    • 1
  • Marek Kulbacki
    • 1
  • Jakub Segen
    • 1
  • Dawid Świątkowski
    • 1
  • Kamil Wereszczyński
    • 1
    • 2
  1. 1.Polish-Japanese Academy of Information TechnologyWarszawaPoland
  2. 2.Institute of InformaticsSilesian University of TechnologyGliwicePoland

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