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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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Correspondence to Sugandhi K. .

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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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