Chalearn Looking at People 2014
ChaLearn organizes in 2014 three parallel challenge tracks on Human Pose Recovery on RGB data, action/interaction spotting on RGB data, and gesture spotting on RGB-Depth data.
Top three ranked participants on each track will be awarded and invited to follow the workshop submission guide for ECCV workshop for inclusion of a description of their system at the ECCV workshop proceedings and submit an extended paper in a special issue on gesture recognition at a high-impact factor journal.
This is a skill-based contest and chance plays no part in the determination of the winner(s). The goal of the contest is split into three competition tracks (with a shared schedule):
Focus of the Contest: More than 8,000 frames of continuous RGB sequences are recorded and labeled with the objective of performing human pose recovery by means of recognizing more than 120,000 human limbs of different people.
Focus of the Contest: Recognizing actions/interactions using 235 performances of 11 action/interaction categories recorded and manually labeled in continuous RGB sequences of different people performing natural isolated and collaborative behaviors.
Focus of the Contest: Recognizing gestures drawn from a vocabulary of Italian sign gesture categories. The emphasis of this 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.
This track follows a previous challenge organized on the same theme: ChaLearn Multi-modal Gesture Recognition 2013. In this new edition, more precise labels are provided, allowing a gesture spotting competition. The data contains more than 900 samples, containing near 14.000 gesture instances and more than 1.4 million of frames.
Python code is provided in order to access the data and evaluate your predictions. Code files are common to all the tracks. See source code reference within each track.
Define the classes and methods to access the data.Download [09/02/2014]
Define the methods for evaluation.Download [09/02/2014]
Each track contains data description, provided code details, and download links. Choose the track tabs for especific information.