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Video analytics is the practice of combining digital video data with machinelearning models to infer various characteristics from that video. Thiscapability has been used for years to detect objects, movement, and the numberof customers in physical retail stores, but more complex machine learningmodels combined with more powerful computing power has unlocked new levels ofpossibility. Researchers claim it is now possible to infer a whole host ofcharacteristics about an individual using video analytics, such as specificage, ethnicity, health status and emotional state. Moreover, an individualsvisual identity can be augmented with information from other data providers tobuild out a detailed profile, all with the individual unknowingly contributingtheir physical presence in front of a retail store camera. Some retailers havebegun to experiment with this new technology as a way to better know theircustomers. However, those same early adopters are caught in an evolving legallandscape around privacy and data ownership. This research looks into thecurrent legal landscape and legislation currently in progress around the use ofvideo analytics, specifically in the retail store setting. Because the ethicaland legal norms around individualized video analytics are still heavily influx, retailers are urged to adopt a wait and see approach or potentially incurcostly legal expenses and risk damage to their brand.

Visual Privacy: Current and Emerging Regulations Around Unconsented Video Analytics in Retail