دورية أكاديمية
AI based monitoring violent action detection data for in-vehicle scenarios
| العنوان: | AI based monitoring violent action detection data for in-vehicle scenarios |
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| المؤلفون: | Nelson R.P. Rodrigues, Nuno M.C. da Costa, Rita Novais, Jaime Fonseca, Paulo Cardoso, João Borges |
| المصدر: | Data in Brief, Vol 45, Iss , Pp 108564- (2022) |
| بيانات النشر: | Elsevier, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Science (General) |
| مصطلحات موضوعية: | Action recognition, Autonomous vehicles, Deep learning, Violent action, Dataset, Computer applications to medicine. Medical informatics, R858-859.7, Science (General), Q1-390 |
| الوصف: | 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. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2352-3409 |
| Relation: | http://www.sciencedirect.com/science/article/pii/S2352340922007715; https://doaj.org/toc/2352-3409 |
| DOI: | 10.1016/j.dib.2022.108564 |
| URL الوصول: | https://doaj.org/article/39d70fbba5df49a1b3eedc6634d22d31 |
| رقم الأكسشن: | edsdoj.39d70fbba5df49a1b3eedc6634d22d31 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 23523409 |
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| DOI: | 10.1016/j.dib.2022.108564 |