This ‘adversarial’ pattern can prevent surveillance cameras from detecting you
- ID
- 12419
- Status
- summarized
- Published
- 09 Aug 2026, 10:00 PM
- Fetched
- 09 Aug 2026, 10:40 PM
- Provider
- TechCrunch
- Category
- technology
- Original URL
- https://techcrunch.com/2026/08/09/this-adversarial-pattern-can-prevent-surveillance-cameras-from-detecting-you/
- Source URL
- https://techcrunch.com/feed/
Summary
- Score
- 4.0
- Created
- 09 Aug 2026, 10:42 PM
- Tags
- Audience
- ai_ml_learnersdevelopers
What happened
Bill Swearingen ran roughly 31 million tests to generate adversarial visual patterns that, when printed on clothing or vehicles, prevent common surveillance cameras and license plate readers from detecting the covered objects or people. He demonstrated the project, called noRecognition, at Def Con 2026 in Las Vegas, showing it can defeat real-world detection algorithms without blocking the cameras from recording video itself.
Why it matters
For AI/ML learners and builders working on computer vision, this is a concrete, real-world demonstration of adversarial examples against deployed surveillance systems—useful as a case study if you build or evaluate object-detection models, but not something most developers or founders need to act on immediately.
Discussion angle
How robust are the object-detection models you ship against physical adversarial patterns, and does this kind of evasion matter for any CV-based product or service you build?