TY  - CONF
AU  - Sergio Escalera
AU  - Xavier Baro
AU  - Jordi Gonzalez
AU  - Miguel Angel Bautista
AU  - Meysam Madadi
AU  - Miguel Reyes
AU  - Victor Ponce
AU  - Hugo Jair Escalante
AU  - Jaime Shotton
AU  - Isabelle Guyon
A2  - ECCVW
PY  - 2014//
TI  - ChaLearn Looking at People Challenge 2014: Dataset and Results
T2  - LNCS
BT  - ECCV Workshop on ChaLearn Looking at People
SP  - 459
EP  - 473
VL  - 8925
KW  - Human Pose Recovery
KW  - Behavior Analysis
KW  - Action and in- teractions
KW  - Multi-modal gestures
KW  - recognition
N2  - This paper summarizes the ChaLearn Looking at People 2014 challenge data and the results obtained by the participants. The competition was split into three independent tracks: human pose recovery from RGB data, action and interaction recognition from RGB data sequences, and multi-modal gesture recognition from RGB-Depth sequences. For all the tracks, the goal was to perform user-independent recognition in sequences of continuous images using the overlapping Jaccard index as the evaluation measure. In this edition of the ChaLearn challenge, two large novel data sets were made publicly available and the Microsoft Codalab platform were used to manage the competition. Outstanding results were achieved in the three challenge tracks, with accuracy results of 0.20, 0.50, and 0.85 for pose recovery, action/interaction recognition, and multi-modal gesture recognition, respectively.
L1  - http://refbase.cvc.uab.es/files/EBG2014.pdf
UR  - http://dx.doi.org/10.1007/978-3-319-16178-5_32
N1  - HuPBA; ISE; 600.063;MV
ID  - Sergio Escalera2014
ER  -