IARPA’s Video LINC program could be repurposed to spy on protesters, enforce 15-minute smart city compliance: perspective The (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. Intelligence Advanced Research Projects Activity Last week, the research funding arm of the US intelligence community, IARPA, published the for its Video Linking and Intelligence from Non-Collaborative Sensors ( ) research program. technical draft Video LINCS The newly-updated draft broad agency announcement and funding opportunity details how the US spy community is looking to autonomously identify, track, and trace people, vehicles, and objects by using footage captured by CCTV cameras, drones, and potentially webcams and phones (as evidenced in the Program Design image below). AI to analyze video Video LINCS “The program will start with person reID, progress to vehicle reID, and culminate with reID of generic objects across a video collection” IARPA Video LINCS Program The official reasons given for developing this program have to do with responding to “ ” that require “ ,” and to “ .” tragic incidents forensic analyses analyze patterns for anomalies and threats IARPA program director Dr. Reuven Meth also mentioned in the video below that would be used to “ .” Video LINCS facilitate smart city planning But ask yourself, why would the US spy agency funding arm want to develop tools for smart city planning? Video LINCS will take labor-intensive workflows and automate them to facilitate forensic analyses, proactive threat detection, and smart city planning” IARPA Program Director Dr. Reuven Meth https://youtu.be/G2U-13OuisU?list=PLfaSGHp0IgDDKoxPpzKw9JvVrozJXxwWt&embedable=true previously reported on the initial on January 9, 2024 when there was limited information publicly available, but last week IARPA updated its technical specs, giving us a more detailed look at just how deep the US spy apparatus is willing to go in its surveillance pursuits. The Sociable Video LINCS program announcement The program consists of two Technical Areas (TAs): Video LINCS : Autonomously and automatically associating the same object (person, vehicle, or generic object) across a video corpus. Re-identification (ReID) : Geo-locating objects to provide positions for all objects in a common world reference frame. Object Geo-localization 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.” “The goal of the Video LINCS program, is to develop re-identification (reID) algorithms to autonomously associate objects across diverse, non-collaborative, video sensor footage and map re-identified objects to a unified coordinate system (geo-localization)” IARPA Video LINCS Program The program, if it does indeed become a fully-funded research program, will consist of three phases over the course of 48 months: Video LINCS During Phase 1, teams will demonstrate the feasibility of reID for people in a video corpus and object geo-localization to provide all subject motion in a common reference frame. (short-term / temporally proximate reID) and provided metadata (e.g. time-stamps and camera pose, to the extent available) will be noise free. Each person’s clothing will remain the same During Phase 2, (long-term / temporally distant reID), , require functionality on generic objects, additional sensor types and collection geometries will be included in the evaluations, and noise will be introduced into provided metadata. reID will expand to include people with clothing changes include vehicles During Phase 3, evaluation , additional sensor types and collection geometries will be included, and there will be greater uncertainty in camera pose. will have a stronger focus on reID of generic objects, temporally distant reID of vehicles will be performed The program will look to re-ID people, vehicles, and objects over long distances and periods of time using a kaleidoscope of technologies, including: Video LINCS Artificial Intelligence Computer vision, including object detection, tracking, person/vehicle/object modeling, generic vision learning Deep learning Geometric camera projections and inverse projections Image and video geo-localization Machine learning Modeling and simulation Open set classification Re-identification Soft biometrics Software engineering Software integration Systems integration Truthed video data collection, annotation (truthing in both anonymized identities and geo-location), including potential Human Subject Research Vehicle fingerprinting Video data generation (including simulation, generative modeling) “The system needs to automatically locate the objects and associate them – across scale, aspect, density, crowding, obscuration, etc. – without introducing false detections and false matches” IARPA Video LINCS Program Apart from threat detection, forensic analyses, and smart city planning, there are many other potential use cases that could come from this spy program down the road. For example, the tools and tactics coming from would be able to, hypothetically, identify who was present at a rally, protest, or riot — such as the one that occurred in Washington, DC on January 6, 2021 — and follow their every move as they make their way back home, even when they change their clothes. Video LINCS Another example could be for keeping at land, air, and sea border crossings. track of immigrants And it would be invaluable to governments wishing to enforce future lockdowns or low-emission zones in as the authorities would be able to identify who broke protocol while tracking and tracing their every move for law enforcement to hunt them down. 15-minute smart cities All of this would be done autonomously and automatically. But hey! maybe I’m being overdramatic. After all, the government said it was to keep people safe, and the government has never let us down in always keeping our best interests at heart. This article was originally published by on Tim Hinchliffe The Sociable.

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US Intelligence Eyes AI and Video Data for Tracking Individuals and Vehicles

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