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Markerless Articulated Human Body Tracking from Multi-view Video with GPU-PSO

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Evolvable Systems: From Biology to Hardware (ICES 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6274))

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Abstract

In this paper, we describe the GPU implementation of a markerless full-body articulated human motion tracking system from multi-view video sequences acquired in a studio environment. The tracking is formulated as a multi-dimensional nonlinear optimisation problem solved using particle swarm optimisation (PSO). We model the human body pose with a skeleton-driven subdivision-surface human body model. The optimisation looks for the best match between the silhouettes generated by the projection of the model in a candidate pose and the silhouettes extracted from the original video sequence. In formulating the solution, we exploit the inherent parallel nature of PSO to formulate a GPU-PSO, implemented within the nVIDIATM CUDATM architecture. Results demonstrate that the GPU-PSO implementation recovers the articulated body pose from 10-viewpoint video sequences with significant computational savings when compared to the sequential implementation, thereby increasing the practical potential of our markerless pose estimation approach.

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Author information

Authors and Affiliations

  1. Dept. of Information Engineering, University of Parma, Italy

    Luca Mussi, Spela Ivekovic & Stefano Cagnoni

  2. Lessells Scholar, Royal Society of Edinburgh, Scotland

    Spela Ivekovic

Authors
  1. Luca Mussi
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  2. Spela Ivekovic
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  3. Stefano Cagnoni
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Editor information

Editors and Affiliations

  1. Department of Electronics, Intelligent Systems Group, University of York, YO10 5DD, York, UK

    Gianluca Tempesti , Andy M. Tyrrell  & Julian F. Miller ,  & 

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Mussi, L., Ivekovic, S., Cagnoni, S. (2010). Markerless Articulated Human Body Tracking from Multi-view Video with GPU-PSO. In: Tempesti, G., Tyrrell, A.M., Miller, J.F. (eds) Evolvable Systems: From Biology to Hardware. ICES 2010. Lecture Notes in Computer Science, vol 6274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15323-5_9

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  • DOI: https://doi.org/10.1007/978-3-642-15323-5_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15322-8

  • Online ISBN: 978-3-642-15323-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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