AI based monitoring violent action detection data for in-vehicle scenarios

• Published in: Data in brief Vol. 45; p. 108564
• Main Authors: Rodrigues, Nelson R.P., da Costa, Nuno M.C., Novais, Rita, Fonseca, Jaime, Cardoso, Paulo, Borges, João
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.12.2022; Elsevier
• Subjects: Action recognition; Autonomous vehicles; Data; data collection; Dataset; Deep learning; humans; skeleton; violence; Violent action; Action recognition; Deep learning; Violent action; Dataset; Autonomous vehicles
• ISSN: 2352-3409; 2352-3409
• DOI: 10.1016/j.dib.2022.108564

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.