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Collection of Visual Data in Climbing Experiments for Addressing the Role of Multi-modal Exploration in Motor Learning Efficiency

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10016))

Abstract

Understanding how skilled performance in human endeavor is acquired through practice has benefited markedly from technologies that can track movements of the limb, body and eyes with reference to the environment. A significant challenge within this context is to develop time efficient methods for observing multiple levels of motor system activity throughout practice. Whilst, activity can be recorded using video based systems, crossing multiple levels of analysis is a substantive problematic within the computer vision and human movement domains. The goal of this work is to develop a registration system to collect movement activity in an environment typical to those that individuals normally seek to participate (sports and physical activities). Detailed are the registration system and procedure to collect data necessary for studying skill acquisition processes during difficult indoor climbing tasks, practiced by skilled climbers. Of particular interest are the problems addressed in trajectory reconstruction when faced with limitations of the registration process and equipment in such unconstrained setups. These include: abrupt movements that violate the common assumption of the smoothness of the camera trajectory; significant motion blur and rolling shutter effects; highly repetitive environment consisting of many similar objects.

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Authors and Affiliations

  1. University of Rouen, Mont-Saint-Aignan, France

    Adam Schmidt, Dominic Orth & Ludovic Seifert

Authors
  1. Adam Schmidt
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  2. Dominic Orth
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  3. Ludovic Seifert
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Corresponding author

Correspondence to Adam Schmidt .

Editor information

Editors and Affiliations

  1. Université Paris-Sud 11 , Orsay, France

    Jacques Blanc-Talon

  2. University of Salento , Lecce, Lecce, Italy

    Cosimo Distante

  3. Ghent University , Gent, Belgium

    Wilfried Philips

  4. CSIRO ICT Centre , Sydney, New South Wales, Australia

    Dan Popescu

  5. University of Antwerp , Wilrijk, Belgium

    Paul Scheunders

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© 2016 Springer International Publishing AG

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Schmidt, A., Orth, D., Seifert, L. (2016). Collection of Visual Data in Climbing Experiments for Addressing the Role of Multi-modal Exploration in Motor Learning Efficiency. In: Blanc-Talon, J., Distante, C., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016. Lecture Notes in Computer Science(), vol 10016. Springer, Cham. https://doi.org/10.1007/978-3-319-48680-2_59

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  • DOI: https://doi.org/10.1007/978-3-319-48680-2_59

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48679-6

  • Online ISBN: 978-3-319-48680-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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