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Explore a conference talk on Privid, a practical system for privacy-preserving video analytics queries. Delve into the challenges of balancing utility and privacy in public surveillance camera footage analysis. Learn about a new notion of differential privacy called (ρ,K,ε)-event-duration privacy, which protects private information visible for less than a specific duration. Discover how Privid enforces duration-based privacy while working with analyst-provided deep neural networks. Examine the system's performance across various videos and queries, comparing its error rates to non-private systems. Gain insights into the query interface, threat model, and key observations made during the research. Understand the potential applications and privacy implications of video analytics in public spaces.
