UoL 3D Social Interaction Dataset

Screenshot of the training environment.

The dataset is composed of 10 sessions. Each session provides RGB-D images and skeleton tracks of 2 long videos of different activities performed by two people. Each session is zipped in a separate file, which contains a folder that has skeleton tracks in a text format and RGB (24 bits) and depth images. Each row of the skeleton text file contains information about positions (6 DoF) of 25 joints.

Title = {Automatic Detection of Human Interactions from RGB-D Data for Social Activity Classification},
Author = {C. Coppola and S. Cosar and D. Faria and N. Bellotto},
Booktitle = {IEEE Int. Symposium on Robot and Human Interactive Communication (RO-MAN)},
Year = {2017},
Pages = {871-876}
Claudio Coppola
Claudio Coppola
Robotics And Machine Learning Scientist

Machine learning and robotics expert with experience in industry and academia applying AI and data science to transportation forecasting, manufacturing automation, robotic perception, and human-robot interaction.