Ling Huang1,2, Hao Zhang1,2, Jiwei Mo1,2, Yuehong Liu1,2, Qiu Lu1,2,*, Shuiwang Li1,2,*
Journal of Information Hiding and Privacy Protection, Vol.7, pp. 45-60, 2025, DOI:10.32604/jihpp.2025.066524
- 31 July 2025
Abstract Rapid advances in computer vision have enabled powerful visual perception systems in areas such as surveillance, autonomous driving, healthcare, and augmented reality. However, these systems often raise serious privacy concerns due to their ability to identify and track individuals without consent. This paper explores the emerging field of identity-hiding visual perception, which aims to protect personal identity within visual data through techniques such as anonymization, obfuscation, and privacy-aware modeling. We provide a system-level overview of current technologies, categorize application scenarios, and analyze major challenges—particularly the trade-off between privacy and utility, technical complexity, and ethical risks. More >