Technical Report of the Video Event Reconstruction and Analysis (VERA) System - Shooter Localization, Models, Interface, and Beyond
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Every minute, hundreds of hours of video are uploaded to social media sites and the Internet from around the world. This material creates a visual record of the experiences of a significant percentage of humanity and can help illuminate how we live in the present moment. When properly analyzed, this video can also help analysts to reconstruct events of interest, including war crimes, human rights violations, and terrorist acts. In this technical report, we describe a newly developed tool, the Video Event Reconstruction and Analysis (VERA) system, that enables the localization of a shooter from just a few videos that include the sound of gunshots using established machine learning techniques and straightforward physics models. This tool relies on other tools we have already developed including video synchronization and geolocation to order unstructured videos lacking metadata over time and space, and sound detection algorithms. Both this gunshot localization tool and the previous systems it incorporates are run through a web interface that enables human-in-the-loop verification to ensure accurate estimations. To demonstrate the efficacy of this suite of tools, we present the results of estimating the shooter's location of the Las Vegas Shooting in 2017 and show that VERA accurately predicts the shooter's location using only the first few gunshots. We then point out future directions that can help improve the system and further reduce unnecessary human labor in the process. All relevant source code, including the web interface and machine learning models, are freely available in Github. We do so in the hope that this tool can be used by anyone who needs it to protect and promote human rights and public safety. We also hope that researchers and software developers will be inspired to improve and expand this system moving forward to better meet the needs of public safety and human rights.
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