日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
arXiv:2505.07766

Privacy Risks of Robot Vision: A User Study on Image Modalities and Resolution

Privacy Risks of Robot Vision: A User Study on Image Modalities and Resolution

シェア:XThreadsFacebookLINEはてブBluesky

著者: Xuying Huang, Sicong Pan, Maren Bennewitz

分類: cs.RO, cs.CV

原文アブストラクト

User privacy is a crucial concern in robotic applications, especially when mobile service robots are deployed in personal or sensitive environments. However, many robotic downstream tasks require the use of cameras, which may raise privacy risks. To better understand user perceptions of privacy in relation to visual data, we conducted a user study investigating how different image modalities and image resolutions affect users' privacy concerns. The results show that depth images are broadly viewed as privacy-safe, and a similarly high proportion of respondents feel the same about semantic segmentation images. Additionally, the majority of participants consider 32*32 resolution RGB images to be almost sufficiently privacy-preserving, while most believe that 16*16 resolution can fully guarantee privacy protection.