PT Unknown
AU Sergio Escalera
   Xavier Baro
   Jordi Gonzalez
   Miguel Angel Bautista
   Meysam Madadi
   Miguel Reyes
   Victor Ponce
   Hugo Jair Escalante
   Jaime Shotton
   Isabelle Guyon
TI ChaLearn Looking at People Challenge 2014: Dataset and Results
BT ECCV Workshop on ChaLearn Looking at People
PY 2014
BP 459
EP 473
VL 8925
DI 10.1007/978-3-319-16178-5_32
DE Human Pose Recovery; Behavior Analysis; Action and in- teractions; Multi-modal gestures; recognition
AB 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.
ER