Reconstructing Human Rights Violations Using Large Eyewitness Video Collections
The Case of Euromaidan Protester Deaths
Bibliographic Data
| ID | 12930360 |
|---|---|
| Authors | Jay D Aronson (corresponding author), McKenna Cole, Alex Hauptmann, Dan Miller, Bradley Samuels |
| Year | 2018 |
| Volume | 10 |
| Issue | 1 |
| Pages | 159-178 |
| Publication date | 2018-02-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Human Rights Practice (JOURNAL) |
| Journal identifiers | ISSN: 1757-9619 • E-ISSN: 1757-9627 |
| Publisher | Oxford University Press (OUP) (PUBLISHER) |
| DOI | 10.1093/jhuman/huy005 |
| OpenAlex | W2801286085 |
| Language | EN |
| Citations received | 4 |
| References cited | 10 |
The widespread availability of mobile phones with high quality cameras means that events around the world can be live streamed or captured on video and rapidly shared via social media. Because this video is multi-perspectival, it can tell the story of an event from many different vantage points, providing a synthetic and composite form of documentation that has the potential to enrich our understanding of events of interest. While video has the potential to provide valuable information, variability in recording platforms and metadata can make a large video archive complex and very difficult to analyse. This paper describes a platform developed by a multidisciplinary team to organize and analyse a large collection of event-based video. It also explains how the system is being deployed to aid in the investigation of allegations of abuses by security forces during the 2013–2014 Euromaidan Protests in Kiev, Ukraine. This platform includes a video archiving system, semi-automated tools for video synchronization and geolocation, and visual interfaces for exploring video data. This system will be useful for the investigation and analysis of protests and demonstrations, mass government repression, police brutality, conflict events, and disasters. The paper concludes by noting that video—even in high volume—does not tell the entire story of an event. As with all other forms of evidence, it must be combined with other available data and relevant knowledge in order to provide a nuanced understanding of what has taken place
Data science · Event (particle physics · Geolocation · Metadata · Selfie · Social media · World Wide Web · Advanced Image and Video Retrieval Techniques · Computer Science · Digital Media Forensic Detection · Video Analysis and Summarization
| Unique citing works | 4 |
|---|---|
| Citations per year | 0,57 |
| Citation span | 2019 - 2025 (7) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 4 |