MIRAGE: Full-Body Bystander Privacy for Smart Glasses with Consent-Based Restoration

arXiv:2609.24537 · cs.CV, cs.CR · Submitted 2026-09-21 · Read on arXiv

cs.CV, cs.CR

Submitted: 2026-09-21

Updated: 2026-09-21

Code: https://github.com/SYSNET-LUMS/MIRAGE

License: http://creativecommons.org/licenses/by/4.0/

The gist: Video recording on smart glasses exposes more than faces.

Terminology

Abstract

Video recording on smart glasses exposes more than faces. Continuous capture reveals full-body biometric signatures, including gait, posture, and silhouette, that enable person re-identification (ReID) even after conventional face sanitization. We present MIRAGE, a three-tier architecture for privacy-preserving smart glasses that enforces full-body privacy, supports synthetic full-body replacement, and retains encrypted recovery material for consent-based restoration. We implement MIRAGE on a Raspberry Pi 5 (a CPU-only proxy for smart-glasses compute), companion phones, and a cloud generative backend. Compared to prior systems, MIRAGE achieves 0.948 AP and 0.976 AR while accurately detecting the complete visible body. Its bounding box masking reduces learned silhouette-based ReID to essentially random guessing, with 10.86% Rank-1 accuracy compared with an 11.12% measured chance level. Even against an adaptive adversary retrained on MIRAGE's sanitized pose signals, Rank-1 gait identification drops from 90.25% to 26.20%, removing 72.5% of the adversary's identification advantage.

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