Real-Time Body Gestures Recognition Using Training Set Constrained Reduction

  • Fabrizio Milazzo
  • Vito Gentile
  • Antonio Gentile
  • Salvatore Sorce
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 611)

Abstract

Gesture recognition is an emerging cross-discipline research field, which aims at interpreting human gestures and associating them to a well-defined meaning. It has been used as a mean for supporting human to machine interaction in several applications of robotics, artificial intelligence, and machine learning. In this paper, we propose a system able to recognize human body gestures which implements a constrained training set reduction technique. This allows the system for a real-time execution. The system has been tested on a publicly available dataset of 7,000 gestures, and experimental results have highlighted that at the cost of a little decrease in the maximum achievable recognition accuracy, the required time for recognition can be dramatically reduced.

Keywords

Gesture recognition Real-time systems Constrained optimization 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Fabrizio Milazzo
    • 1
  • Vito Gentile
    • 1
  • Antonio Gentile
    • 1
  • Salvatore Sorce
    • 1
  1. 1.Ubiquitous Systems and Interfaces Group (USI)Università degli Studi di Palermo-Dipartimento dell’Innovazione Industriale e Digitale (DIID)PalermoItaly

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