ChaLearn multi-modal gesture recognition 2013

Sergio Escalera, Cristian Sminchisescu, Richard Bowden, Stan Sclaroff, Jordi Gonzàlez, Xavier Baró, Miguel Reyes, Isabelle Guyon, Vassilis Athitsos, Hugo Escalante, Leonid Sigal, Antonis Argyros
<span title="">2013</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="" style="color: black;">Proceedings of the 15th ACM on International conference on multimodal interaction - ICMI &#39;13</a> </i> &nbsp;
We organized a Grand Challenge and Workshop on Multi-Modal Gesture Recognition. 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 Kinect T M camera. More than 54 teams participated in the challenge and a final error rate of 12% was achieved by the
more &raquo; ... nner of the competition. Winners of the competition published their work in the workshop of the Challenge. The MMGR Workshop was held at ICMI conference 2013, Sidney. A total of 9 relevant papers with basis on multi-modal gesture recognition were accepted for presentation. This includes multi-modal descriptors, multi-class learning strategies for segmentation and classification of temporal data, as well as relevant applications in the field, including multi-modal Social Signal Processing and multimodal Human Computer Interfaces.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1145/2522848.2532597</a> <a target="_blank" rel="external noopener" href="">dblp:conf/icmi/EscaleraGBRGAESASBS13</a> <a target="_blank" rel="external noopener" href="">fatcat:tx5jk4bdjjaohk3n4brrj62e4y</a> </span>
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