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Benefits of Gaussian Convolution in Gait Recognition

Author:
Marsico, Maria De [DBLP] ;
Mecca, Alessio [DBLP]
Abstract
The first and still popular approach to gait recognition applies computer vision techniques to appearance-based features of walking patterns. More recently, wearable sensors have become attractive. The accelerometer is the most used one, being embedded in widespread mobile devices. Related techniques do not suffer for problems like occlusion and point of view, but for intra-subject variations caused by walking speed, ground type, shoes, etc. However, we can often recognize a person from the walking pattern, and this stimulates to search for robust features, able to sufficiently characterize this trait. This paper presents some preliminary experiments using the convolution with Gaussian kernels to extract relevant gait elements. The experiments use the large ZJU-gaitacc public dataset, and achieve improved results compared with previous works exploiting the same dataset.
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Marsico, M. D. & Mecca, A., (2018). Benefits of Gaussian Convolution in Gait Recognition. In: Brömme, A., Busch, C., Dantcheva, A., Rathgeb, C. & Uhl, A. (Hrsg.), BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group. Bonn: Köllen Druck+Verlag GmbH.
@inproceedings{mci/Marsico2018,
author = {Marsico, Maria De AND Mecca, Alessio},
title = {Benefits of Gaussian Convolution in Gait Recognition},
booktitle = {BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group},
year = {2018},
editor = {Brömme, Arslan AND Busch, Christoph AND Dantcheva, Antitza AND Rathgeb, Christian AND Uhl, Andreas},
publisher = {Köllen Druck+Verlag GmbH},
address = {Bonn}
}
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More Info

ISBN: 978-3-88579-676-4
ISSN: 1617-5469
xmlui.MetaDataDisplay.field.date: 2018
Language: en (en)
Content Type: Text/Conference Paper

Keywords

  • Gait Recognition
  • Biometrics
  • Gaussian Kernel
Collections
  • P282 - BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group [32]

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Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.