The intelligence community is working on amping up people-recognition power to spot, in live videos, shooters and potential terrorists before they have a chance to attack.
Part of the problem with current video surveillance techniques is the difficulty of recognizing objects and people, simultaneously, in real-time.
But Deep Intermodal Video Analytics, or DIVA, a research project out of the Office of the Director of National Intelligence, will attempt to automatically detect suspicious activities, with the help of live video pouring in through multiple camera feeds.
ODNI’s Intelligence Advanced Research Projects Agency is gathering academics and private sector experts for a July 12 “Proposers’ Day,” in anticipation of releasing a work solicitation.
“The DIVA program will produce a common framework and software prototype for activity detection, person/object detection and recognition across a multicamera network,” IARPA officials said in a synopsis of the project published June 3. “The impact will be the development of tools for forensic analysis, as well as real-time alerting for user-defined threat scenarios.”
In other words, the tech would scour incoming video surveillance and body-camera imagery from areas of interest for people and objects who could present a threat, or individuals and items that might have been involved in a past crime.
This is the type of video-recognition system that might have been used for identifying would-be suicide bombers before the Paris and Brussels attacks, some video analytics experts say.
Privacy laws in the United States and Europe differ, so it is unclear whether such activity-recognition software would have been legal to use…