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Feature Extraction Methods for Human Gait Recognition – A Survey

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Advances in Computing and Data Sciences (ICACDS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 721))

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Abstract

Human gait recognition opens a wide variety of challenging problems for research community. Feature extraction has a significant role in designing human gait recognition systems. Numerous features have been defined based on gait video frames. Spatial as well as temporal descriptors have equal importance within gait features. In this paper, we present a survey of prominent feature extraction methods incorporated in human gait recognition systems and their respective recognition accuracies are reported. Also, a description of popular gait databases is presented.

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Acknowledgement

The authors would like to acknowledge Department of Science and Technology (DST), New Delhi, India for the financial support extended under the INSPIRE Fellowship scheme.

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Authors and Affiliations

  1. Department of Information Technology, Kannur University, Kannur, Kerala, India

    Sugandhi K., Farha Fatina Wahid & Raju G.

Authors
  1. Sugandhi K.
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  2. Farha Fatina Wahid
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  3. Raju G.
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Corresponding author

Correspondence to Sugandhi K. .

Editor information

Editors and Affiliations

  1. Krishna Engineering College, Ghaziabad, Uttar Pradesh, India

    Mayank Singh

  2. Jaypee University of Information Technology, Waknaghat, Himachal Pradesh, India

    P.K. Gupta

  3. Department of Computer Science and Engineering, Raghogarh, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

    Vipin Tyagi

  4. Indira Gandhi Delhi Technical University, New Delhi, India

    Arun Sharma

  5. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, Ontario, Canada

    Tuncer Ören

  6. Department of Computer and Information Science, University of Michigan-Dearborn, Dearborn, Michigan, USA

    William Grosky

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K., S., Wahid, F.F., G., R. (2017). Feature Extraction Methods for Human Gait Recognition – A Survey. In: Singh, M., Gupta, P., Tyagi, V., Sharma, A., Ören, T., Grosky, W. (eds) Advances in Computing and Data Sciences. ICACDS 2016. Communications in Computer and Information Science, vol 721. Springer, Singapore. https://doi.org/10.1007/978-981-10-5427-3_40

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  • DOI: https://doi.org/10.1007/978-981-10-5427-3_40

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5426-6

  • Online ISBN: 978-981-10-5427-3

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