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Vision Based Gait Analysis for Frontal View Gait Sequences Using RGB Camera

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Ubiquitous Computing and Ambient Intelligence (UCAmI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10069))

Abstract

In this paper we propose a vision based gait analysis approach to work with frontal view sequences. The main issue of sagittal view gait sequences is the physical space required to record them. We propose two different approaches to obtain heel strike and toe off with frontal gait, both of them are based in the time series of the difference of component y of both feet. In the former, the zero crosses are used to determine the range in which heel strike and toe off occurs. In the latter, the maxima and minima are used instead. Testing our approach with our own dataset show that it is possible to obtain heel strike and toe off events using only frontal view gait sequences recorded with an RGB camera. Results show as well that it is possible to classify between normal and abnormal gait using frontal view.

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Acknowledgements

This research is part of the FRASE MINECO project (TIN2013-47152-C3-2-R) funded by the Ministry of Economy and Competitiveness of Spain.

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Authors and Affiliations

  1. Department of Computing Technology, University of Alicante, Campus San Vicente del Raspeig, Alicante, Spain

    Mario Nieto-Hidalgo, Francisco Javier Ferrández-Pastor, Rafael J. Valdivieso-Sarabia, Jerónimo Mora-Pascual & Juan Manuel García-Chamizo

Authors
  1. Mario Nieto-Hidalgo
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  2. Francisco Javier Ferrández-Pastor
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  3. Rafael J. Valdivieso-Sarabia
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  4. Jerónimo Mora-Pascual
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  5. Juan Manuel García-Chamizo
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Corresponding author

Correspondence to Mario Nieto-Hidalgo .

Editor information

Editors and Affiliations

  1. University of Las Palmas de Gran Canaria, Las Palmas, Spain

    Carmelo R. García

  2. Departamento de Estadistica, Universidad La Laguna, La Laguna, Spain

    Pino Caballero-Gil

  3. Florida State University, Tallahassee, Florida, USA

    Mike Burmester

  4. University of Las Palmas de Gran Canaria, Las Palmas, Spain

    Alexis Quesada-Arencibia

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Nieto-Hidalgo, M., Ferrández-Pastor, F.J., Valdivieso-Sarabia, R.J., Mora-Pascual, J., García-Chamizo, J.M. (2016). Vision Based Gait Analysis for Frontal View Gait Sequences Using RGB Camera. In: García, C., Caballero-Gil, P., Burmester, M., Quesada-Arencibia, A. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2016. Lecture Notes in Computer Science(), vol 10069. Springer, Cham. https://doi.org/10.1007/978-3-319-48746-5_3

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  • DOI: https://doi.org/10.1007/978-3-319-48746-5_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48745-8

  • Online ISBN: 978-3-319-48746-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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