Results and Analysis of ChaLearn LAP Multi-Modal Isolated and Continuous Gesture Recognition, and Real Versus Fake Expressed Emotions Challenges

Jun Wan, Sergio Escalera, Gholamreza Anbarjafari, Hugo Jair Escalante, Xavier Baro, Isabelle Guyon, Meysam Madadi, Juri Allik, Jelena Gorbova, Chi Lin, Yiliang Xie; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017, pp. 3189-3197

We analyze the results of the 2017 ChaLearn Looking at People Challenge at ICCV. The challenge comprised three tracks: (1) large-scale isolated (2) continuous gesture recognition, and (3) real versus fake expressed emotions tracks. It is the second round for both gesture recognition challenges, which were held first in the context of the ICPR 2016 workshop on "multimedia challenges beyond visual analysis". In this second round, more participants joined the competitions, and the performances considerably improved compared to the first round. The third track is the first challenge on real versus fake expressed emotion classification, including six emotion categories, for which a novel database was introduced. The first place was shared between two teams who achieved 67.7 averaged recognition rate on the test set. The data of the three tracks, the participants' code and method descriptions are publicly available to allow researchers to keep making progress in the field.