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Multi-scale Deep Learning for Gesture Detection and Localization

  • Natalia NeverovaEmail author
  • Christian Wolf
  • Graham W. Taylor
  • Florian Nebout
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8925)

Abstract

We present a method for gesture detection and localization based on multi-scale and multi-modal deep learning. Each visual modality captures spatial information at a particular spatial scale (such as motion of the upper body or a hand), and the whole system operates at two temporal scales. Key to our technique is a training strategy which exploits i) careful initialization of individual modalities; and ii) gradual fusion of modalities from strongest to weakest cross-modality structure. We present experiments on the ChaLearn 2014 Looking at People Challenge gesture recognition track, in which we placed first out of 17 teams.

Keywords

Gesture recognition Multi-modal systems Deep learning 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Natalia Neverova
    • 1
    • 2
    Email author
  • Christian Wolf
    • 1
    • 2
  • Graham W. Taylor
    • 3
  • Florian Nebout
    • 4
  1. 1.Université de Lyon, CNRSLyonFrance
  2. 2.INSA-Lyon, LIRIS, UMR5205Villeurbanne cedexFrance
  3. 3.University of GuelphGuelphCanada
  4. 4.AwabotLyonFrance

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