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Detection of Clothes Change Fusing Color, Texture, Edge and Depth Information

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E-Business and Telecommunications (ICETE 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 554))

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Abstract

Changing clothes is a basic activity of daily living (ADL) which may be used as a measurement of the functional status of e.g. an elderly person, or a person with certain disabilities. In this paper we propose a methodology for the detection of when a human has changed clothes. Our non-contact unobtrusive monitoring system is built upon the Microsoft Kinect depth camera. It uses the OpenNI SDK to detect a human skeleton and extract the upper and lower clothes’ visual features. Color, texture and edge descriptors are then extracted and fused. We evaluate our system on a publicly available set of real recordings for several users and under various illumination conditions. Our results show that our system is able to successfully detect when a user changes clothes, thus to assess the quality of the corresponding ADL.

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Notes

  1. 1.

    (http://users.iit.demokritos.gr/~tyianak/ClothesCode.html)

  2. 2.

    “positive” refers to clothes change detection, therefore “negative” means “no clothes change”.

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Acknowledgements

The research leading to these results has received funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no 288532. For more details, please see http://www.usefil.eu.

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Authors and Affiliations

  1. Computational Intelligence Laboratory (CIL), Institute of Informatics and Telecommunications, National Center for Scientific Research–DEMOKRITOS, Patriarchou Grigoriou & Neapoleos, 15310, Agia Paraskevi, Athens, Greece

    Dimitrios Sgouropoulos, Theodoros Giannakopoulos, Giorgos Siantikos, Evaggelos Spyrou & Stavros Perantonis

Authors
  1. Dimitrios Sgouropoulos
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  2. Theodoros Giannakopoulos
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  3. Giorgos Siantikos
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  4. Evaggelos Spyrou
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  5. Stavros Perantonis
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Corresponding author

Correspondence to Dimitrios Sgouropoulos .

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Editors and Affiliations

  1. Rose Hill and Lincoln Center Campuses, Fordham University, Bronx, New York, USA

    Mohammad S. Obaidat

  2. Medical Informatis, Statistics, Document, Medical University Graz, Graz, Austria

    Andreas Holzinger

  3. INSTICC, Polytechnic Institute of Setúbal, Setúbal, Portugal

    Joaquim Filipe

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Sgouropoulos, D., Giannakopoulos, T., Siantikos, G., Spyrou, E., Perantonis, S. (2015). Detection of Clothes Change Fusing Color, Texture, Edge and Depth Information. In: Obaidat, M., Holzinger, A., Filipe, J. (eds) E-Business and Telecommunications. ICETE 2014. Communications in Computer and Information Science, vol 554. Springer, Cham. https://doi.org/10.1007/978-3-319-25915-4_20

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  • DOI: https://doi.org/10.1007/978-3-319-25915-4_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25914-7

  • Online ISBN: 978-3-319-25915-4

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