Published October 2, 2023
| Version 1.0
Dataset
Open
Real and Synthetic Dataset for Active Shooter Situations
Authors/Creators
- 1. Department of Mechanical Engineering, Iowa State University, Ames, IA 50011, USA
- 2. Department of Mechanical Engineering, University of Tennessee, Knoxville, TN 37996, USA
- 3. Department of Computer Science, Iowa State University, Ames, IA 50011, USA
Description
This dataset includes annotations for shooters (both person and visible portion of the gun) and guns in a primarily indoor setting. The synthetic data was generated using Unreal Engine 4 and Unreal Engine 5 and contains both the default semi-realistic textures of the environments and segmentation masks as a form of domain randomization. The textured synthetic data was further augmented with camera sensor effects as another domain adaptation technique. The folders use the following notation: T denotes textured synthetic, M denotes masked synthetic, R denotes real, and the prefix A denotes augmented. We also include some annotated videos for evaluating tracking performance.
Files
Real and Synthetic Dataset for Active Shooter Situations.zip
Additional details
Funding
- U.S. National Science Foundation
- CPS: Medium: Collaborative Research: Active Shooter Tracking & Evacuation Routing for Survival (ASTERS) 1932505
- U.S. National Science Foundation
- CPS: Medium: Collaborative Research: Active Shooter Tracking & Evacuation Routing for Survival (ASTERS) 1932033