Large Scale Audio-Visual Video Analytics Platform for Forensic Investigations of Terroristic Attacks
This addresses a critical problem for law enforcement agencies in forensic investigations, though it appears incremental as it integrates existing analytical modules into a scalable architecture.
The paper tackles the challenge of analyzing thousands of hours of video footage in terrorist attack investigations by developing a platform that fuses audio and visual analytics from surveillance and eyewitness videos to index content based on attack-specific concepts, enabling rapid investigation starts.
The forensic investigation of a terrorist attack poses a huge challenge to the investigative authorities, as several thousand hours of video footage need to be spotted. To assist law enforcement agencies (LEA) in identifying suspects and securing evidences, we present a platform which fuses information of surveillance cameras and video uploads from eyewitnesses. The platform integrates analytical modules for different input-modalities on a scalable architecture. Videos are analyzed according their acoustic and visual content. Specifically, Audio Event Detection is applied to index the content according to attack-specific acoustic concepts. Audio similarity search is utilized to identify similar video sequences recorded from different perspectives. Visual object detection and tracking are used to index the content according to relevant concepts. The heterogeneous results of the analytical modules are fused into a distributed index of visual and acoustic concepts to facilitate rapid start of investigations, following traits and investigating witness reports.