A survey of video datasets for human action and activity recognition

  • Authors:
  • Jose M. Chaquet;Enrique J. Carmona;Antonio Fernández-Caballero

  • Affiliations:
  • Dpto. de Inteligencia Artificial, Escuela Técnica Superior de Ingeniería Informática, Universidad Nacional de Educación a Distancia, 28040 Madrid, Spain;Dpto. de Inteligencia Artificial, Escuela Técnica Superior de Ingeniería Informática, Universidad Nacional de Educación a Distancia, 28040 Madrid, Spain;Instituto de Investigación en Informática de Albacete, Universidad de Castilla-La Mancha, 02071 Albacete, Spain

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2013

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Abstract

Vision-based human action and activity recognition has an increasing importance among the computer vision community with applications to visual surveillance, video retrieval and human-computer interaction. In recent years, more and more datasets dedicated to human action and activity recognition have been created. The use of these datasets allows us to compare different recognition systems with the same input data. The survey introduced in this paper tries to cover the lack of a complete description of the most important public datasets for video-based human activity and action recognition and to guide researchers in the election of the most suitable dataset for benchmarking their algorithms.