Multi-modal gesture recognition challenge 2013: Dataset and results



The recognition of continuous natural gestures is a complex and challenging problem due to the multi-modal nature of involved visual cues (eg fingers and lips movements, subtle facial expressions, body pose, etc.), as well as technical limitations such as spatial and temporal resolution and unreliable depth cues. In order to promote the research advance on this field, we organized a challenge on multi-modal gesture recognition. We made available a large video database of 13,858 gestures from a lexicon of 20 Italian gesture categories recorded with a Kinect™ camera, providing the audio, skeletal model, user mask, RGB and depth images. The focus of the challenge was on user independent multiple gesture learning. There are no resting positions and the gestures are performed in continuous sequences lasting 1-2 minutes, containing between 8 and 20 gesture instances in each sequence. As a result, the …


Vassilis Athitsos
Jordi Gonzàlez
Xavier Baró
Miguel Reyes
Oscar Lopes
Isabelle Guyon
Isabelle Guyon
Sergio Escalera