Citation

Rodrigues NRP, da Costa NMC, Novais R, Fonseca J, Cardoso P, Borges J. Data Brief 2022; 45: e108564.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.dib.2022.108564

PMID

36188137

PMCID

PMC9519434

Abstract

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.

Language: en

Keywords

Dataset; Autonomous vehicles; Deep learning; Action recognition; Violent action