Track description

More than 14,000 gestures are drawn from a vocabulary of 20 Italian sign gesture categories. The emphasis of this third track is on multi-modal automatic learning of a set of 20 gestures performed by several different users, with the aim of performing user independent continuous gesture spotting.

For each sample, RGB, depth, user segmentation and skeleton information are provided:

Chalearn LAP 2014. Track 3 data modalities

A more detailed information is provided on the data section of the competition.


Provided Resources

  • Scripts: With the data, the organizers provides a set of scripts to facilitate the access to the data and use the evaluation metrics. More information is provided on the data page.
  • Contact: In order to clarify any doubt or to ask general assistance, you can contact the organizers at or use the forum on data description page.


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