On-demand Forensic Video Analytics for Large-Scale Surveillance Systems

This work presents FOVEA, an add-on suite of analytic tools for the forensic review of video in large-scale surveillance systems. While significant investment has been made toward improving camera coverage and quality, the burden on video operators for reviewing and extracting useful information from the video has only increased. Daily investigation tasks (such as searching through video, investigating abandoned objects, or piecing together information from multiple cameras) still require a significant amount of manual review by video operators. In contrast to other tools which require exporting video data or otherwise curating the video collection before analysis, FOVEA is designed to integrate with existing surveillance systems. Tools can be applied to any video stream in an on-demand fashion without additional hardware. This paper details the technical approach, underlying algorithms, and effects on video operator performance.