Workshop description

ChaLearn organizes in 2013 a challenge and workshop on multi-modal gesture recognition from 2D and 3D video data using Kinect, in conjunction with ICMI 2013, December 9-13, Sidney, Australia. Kinect is revolutionizing the field of gesture recognition given the set of input data modalities it provides, including RGB image, depth image (using an infrared sensor), and audio. Gesture recognition is genuinely important in many multi-modal interaction and computer vision applications, including image/video indexing, video surveillance, computer interfaces, and gaming. It also provides excellent benchmarks for algorithms. The recognition of continuous, natural signing is very challenging due to the multimodal nature of the visual cues (e.g., movements of fingers and lips, facial expressions, body pose), as well as technical limitations such as spatial and temporal resolution and unreliable depth cues. The workshop is devoted to the presentation of most recent and challenging techniques from multi-modal gesture recognition. The committee encourages paper submissions in the following topics (but not limited to):

  • Multi-modal descriptors for gesture recognition
  • Fusion strategies for gesture recognition
  • Multi-modal learning for gesture recognition
  • Data sets and evaluation protocols for multi-modal gesture recognition
  • Applications of multi-modal gesture recognition

The results of the challenge will be discussed at the workshop. It features a quantitative evaluation of automatic gesture recognition from a multi-modal dataset recorded with Kinect (providing RGB images of face and body, depth images of face and body, skeleton information, joint orientation and audio sources), including about 20,000 gestures from several users. The gestures are drawn from different gesture vocabularies from very diverse domains. The emphasis of the competition is on multi-modal automatic learning of vocabularies of gestures performed by several different users, with the aim of performing user independent continuous gesture recognition.

Additionally, the challenge includes a live competition of demos/systems of applications based on multi-modal gesture recognition techniques. Demos using data from different modalities and different kind of devices are welcome. The demos will be evaluated in terms of multi-modality, technical quality, and applicability.

Best workshop papers and top three ranked participants of the quantitative evaluation will be invited to present their work at ICMI 2013 and their papers will be published in the proceedings. Additionally, there will be travel grants (based on availability) and the possibility to be invited to present extended versions of their works to a special issue in a high impact factor journal. Moreover, all three top ranking participants in the quantitative challenge will be awarded with a ChaLearn winner certificate and an economic prize (based on availability). We will also announce a best paper and best student paper awards among the workshop contributions.

The ChaLearn Challenge organisers have negotiated a Special Topic on Gesture Recognition call for papers with the Journal of Machine Learning Research. More details can be found in this downloadable call for papers.


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