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.
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.
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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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
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