Video content analysis on body-worn cameras for retrospective investigation

In the security domain, cameras are important to assess critical situations. Apart from fixed surveillance cameras we observe an increasing number of sensors on mobile platforms, such as drones, vehicles and persons. Mobile cameras allow rapid and local deployment, enabling many novel applications and effects, such as the reduction of violence between police and citizens. However, the increased use of bodycams also creates potential challenges. For example: how can end-users extract information from the abundance of video, how can the information be presented, and how can an officer retrieve information efficiently? Nevertheless, such video gives the opportunity to stimulate the professionals’ memory, and support complete and accurate reporting. In this paper, we show how video content analysis (VCA) can address these challenges and seize these opportunities. To this end, we focus on methods for creating a complete summary of the video, which allows quick retrieval of relevant fragments. The content analysis for summarization consists of several components, such as stabilization, scene selection, motion estimation, localization, pedestrian tracking and action recognition in the video from a bodycam. The different components and visual representations of summaries are presented for retrospective investigation.