  The forensic investigation of a terrorist attack poses a significant
challenge to the investigative authorities, as often several thousand hours of
video footage must be viewed. Large scale Video Analytic Platforms (VAP) assist
law enforcement agencies (LEA) in identifying suspects and securing evidence.
Current platforms focus primarily on the integration of different computer
vision methods and thus are restricted to a single modality. We present a video
analytic platform that integrates visual and audio analytic modules and fuses
information from surveillance cameras and video uploads from eyewitnesses.
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. Innovative user-interface concepts are introduced to harness
the full potential of the heterogeneous results of the analytical modules,
allowing investigators to more quickly follow-up on leads and eyewitness
reports.
