Chalearn multi-modal gesture recognition 2013: grand challenge and workshop summary

2013

Abstract

The MMGR Grand Challenge focused on the recognition of continuous natural gestures from multi-modal data (including RGB, Depth, user mask, Skeletal model, and audio). We made available a large labeled video database of 13, 858 gestures from a lexicon of 20 Italian gesture categories recorded with a KinectTM camera. More than 54 teams participated in the challenge and a final error rate of 12% was achieved by the winner of the competition. Winners of the competition published their work in the workshop of the Challenge.

Authors

Vassilis Athitsos
Jordi Gonzàlez
Xavier Baró
Miguel Reyes
Isabelle Guyon
Leonid Sigal
Sergio Escalera
Cristian Sminchisescu
Hugo Jair Escalante
Stan Sclaroff
Richard Bowden
Isabelle Guyon