TY  - JOUR
PY  - 2022//
TI  - AI based monitoring violent action detection data for in-vehicle scenarios
JO  - Data in brief
A1  - Rodrigues, Nelson R. P.
A1  - da Costa, Nuno M. C.
A1  - Novais, Rita
A1  - Fonseca, Jaime
A1  - Cardoso, Paulo
A1  - Borges, João
SP  - e108564
EP  - e108564
VL  - 45
IS  - 
N2  - With the evolution of technology associated with mobility and autonomy, Shared Autonomous Vehicles will be a reality. To ensure passenger safety, there is a need to create a monitoring system inside the vehicle capable of recognizing human actions. We introduce two datasets to train human action recognition inside the vehicle, focusing on violence detection. The InCar dataset tackles violent actions for in-car background which give us more realistic data. The InVicon dataset although doesn't have the realistic background as the InCar dataset can provide skeleton (3D body joints) data. This datasets were recorded with RGB, Depth, Thermal, Event-based, and Skeleton data. The resulting dataset contains 6 400 video samples and more than 3 million frames, collected from sixteen distinct subjects. The dataset contains 58 action classes, including violent and neutral (i.e., non-violent) activities.<p />  <p>Language: en</p>
LA  - en
SN  - 2352-3409
UR  - http://dx.doi.org/10.1016/j.dib.2022.108564
ID  - ref1
ER  -