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“Consider a swarm of bees. One may be interested in knowing a specific bee such as the queen bee. Where is the queen bee throughout the collection? One may also be interested in knowing where the bees travel in general, how far they travel from The Hive, which flowers do they visit etc. Knowing the path of where the bee traveled gives insight into its routine habits. I've been performing R&D in computer vision for well over two decades and I've been part of the transformation from a field that was primarily fundamental research into one that is now part of everyday products. Video LINCS as well will provide new capabilities that were not available previously. It will take labor intensive workflows and automate them to facilitate forensic analyses, proactive threat detection and *Smart City Planning*.” ~ Dr. Reuven Meth From article: “The Intelligence Advanced Research Projects Activity (IARPA) is putting together a research program for the US spy community to autonomously identify, track, and trace people and their vehicles over long distances and periods of time… by using AI to analyze video footage captured by CCTV cameras, drones, and potentially webcams and phones. The official reasons given for developing this program have to do with responding to “tragic incidents” that require “forensic analyses,” and to “analyze patterns for anomalies and threats.” IARPA program director Dr. Reuven Meth also mentioned in the video below that Video LINCS would be used to “facilitate smart city planning.”But ask yourself, why would the US spy agency funding arm want to develop tools for smart city planning? The Video LINCS program consists of two Technical Areas (TAs):* Re-identification (ReID): Autonomously and automatically associating the same object (person, vehicle, or generic object) across a video corpus.* Object Geo-localization: Geo-locating objects to provide positions for all objects in a common world reference frame. ReID, according to IARPA, means “the process of matching the same object across a video collection, to determine where the object appears throughout the video.”