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.

中文翻译：

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用于调查恐怖袭击后情景的多模式视频取证平台

对恐怖袭击的法医调查对调查当局构成了重大挑战，因为通常必须观看数千小时的录像。大型视频分析平台 (VAP) 可协助执法机构 (LEA) 识别嫌疑人和保护证据。当前平台主要关注不同计算机视觉方法的集成，因此仅限于单一模式。我们提出了一个视频分析平台，该平台集成了视觉和音频分析模块，并融合了来自监控摄像头的信息和来自目击者的视频上传。视频根据其声学和视觉内容进行分析。具体而言，音频事件检测用于根据特定于攻击的声学概念对内容进行索引。音频相似性搜索用于识别从不同角度记录的相似视频序列。视觉对象检测和跟踪用于根据相关概念对内容进行索引。引入了创新的用户界面概念，以充分利用分析模块异类结果的全部潜力，使调查人员能够更快地跟进线索和目击者报告。