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

Source: [Privacy Risks of Robot Vision: A User Study on Image Modalities and Resolution](<https://www.sota2.com/research/paper/68fa787a1e209131cea7897b>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T04:39:15.781Z

Authors: Xuying Huang, Sicong Pan, Maren Bennewitz

Published: 2025-05-12T17:16:12.000Z

## Abstract

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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2505.07766>)

[PDF](<https://arxiv.org/pdf/2505.07766.pdf>)