Computer vision is finally working in the real world, but what are the consequences on privacy and security? For example, recent work shows that vision algorithms can spy on smartphone keypresses from meters away, steal information from inside homes via hacked cameras, exploit social media to de-anonymize blurred faces, and reconstruct images from features like SIFT. Vision could also enhance privacy and security, for example through assistive devices for people with disabilities, phishing detection techniques that incorporate visual features, and image forensic tools. Some technologies present both challenges and opportunities: biometrics techniques could enhance security but may be spoofed, while surveillance systems enhance safety but create potential for abuse. We need to understand the potential threats and opportunities of vision to avoid creating detrimental societal effects and/or facing public backlash. This workshop will explore the intersection between computer vision and security and privacy to address these issues.
We welcome original research papers and extended abstracts on topics including but not limited to:
Computer vision-based security and privacy attacks
Biometric spoofing defenses and liveness detection
Impact of ubiquitous cameras on society
Captchas and other visual Turing tests for online security
Privacy of visual data
Privacy-preserving visual features and representations
Reversibility of image transformations
Secure/encrypted computer vision and image processing
Wearable camera privacy
Attacks against computer vision systems
Copyright violation detection
Counterfeit and forgery detection
Privacy implications of large-scale visual social media
Other relevant topics
07月21日
2017
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