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The AVA Multi-View Dataset for Gait Recognition

  • David López-FernándezEmail author
  • Francisco José Madrid-Cuevas
  • Ángel Carmona-Poyato
  • Manuel Jesús Marín-Jiménez
  • Rafael Muñoz-Salinas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8703)

Abstract

In this paper, we introduce a new multi-view dataset for gait recognition. The dataset was recorded in an indoor scenario, using six convergent cameras setup to produce multi-view videos, where each video depicts a walking human. Each sequence contains at least 3 complete gait cycles. The dataset contains videos of 20 walking persons with a large variety of body size, who walk along straight and curved paths. The multi-view videos have been processed to produce foreground silhouettes. To validate our dataset, we have extended some appearance-based 2D gait recognition methods to work with 3D data, obtaining very encouraging results. The dataset, as well as camera calibration information, is freely available for research purposes.

Keywords

Human Gait Gait Recognition Camera Setup Gait Sequence Gait Energy Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work has been developed with the support of the Research Projects called TIN2012-32952 and BROCA both financed by Science and Technology Ministry of Spain and FEDER.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • David López-Fernández
    • 1
    Email author
  • Francisco José Madrid-Cuevas
    • 1
  • Ángel Carmona-Poyato
    • 1
  • Manuel Jesús Marín-Jiménez
    • 1
  • Rafael Muñoz-Salinas
    • 1
  1. 1.Computing and Numerical Analysis Department, Campus de Rabanales, Maimónides Institute for Biomedical Research (IMIBIC)University of CórdobaCórdobaSpain

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