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Visual Analysis of Humans pp 131–137Cite as

Articulated Pose Estimation and Tracking: Introduction

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Abstract

This chapter gives a brief introduction to the problem of human pose recovery from images and/or video. In doing so, it provides the overall context for the remaining chapters in this part of the book. It also gives a brief introduction to some of the relevant topics, in this problem domain, that ended up being out of the scope for the book (e.g., geometric models for pose reconstruction and methods that utilize alternative sensor modalities).

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Notes

  1. 1.

    A realistic generative model for a human hand was introduced in [6]. The model includes shape, appearance, and lighting parameters, and is capable of generating realistic samples.

  2. 2.

    Inference involves figuring out a set of parameters for this model that makes a given observed image, or sequence, very likely.

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Author information

Authors and Affiliations

  1. Disney Research, Pittsburgh, PA, USA

    Leonid Sigal

Authors
  1. Leonid Sigal
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Correspondence to Leonid Sigal .

Editor information

Editors and Affiliations

  1. Department of Media Technology, Aalborg University, Niels Jernes Vej 14, Aalborg, 9220, Denmark

    Thomas B. Moeslund

  2. Centre for Vision, Speech & Signal Proc., University of Surrey, Guildford, GU2 7XH, Surrey, United Kingdom

    Adrian Hilton

  3. Copenhagen Institute of Technology, Aalborg University, Lautrupvang 2B, Ballerup, 2750, Denmark

    Volker Krüger

  4. Disney Research, Forbes Avenue 615, Pittsburgh, 15213, Pennsylvania, USA

    Leonid Sigal

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Sigal, L. (2011). Articulated Pose Estimation and Tracking: Introduction. In: Moeslund, T., Hilton, A., Krüger, V., Sigal, L. (eds) Visual Analysis of Humans. Springer, London. https://doi.org/10.1007/978-0-85729-997-0_8

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  • DOI: https://doi.org/10.1007/978-0-85729-997-0_8

  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-996-3

  • Online ISBN: 978-0-85729-997-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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