Visual navigation is a fundamental capability of

mobile service robots, yet the onboard cameras required for

such navigation can capture privacy-sensitive information and

raise user privacy concerns. Existing approaches to privacy-

preserving navigation-oriented visual perception have largely

been driven by technical considerations, with limited grounding

in user privacy preferences. In this work, we propose a

user-centered approach to designing privacy-preserving visual

perception for robot navigation. To investigate how user privacy

preferences can inform such design, we conducted two user

studies. The results show that users prefer privacy-preserving

visual abstractions and capture-time low-resolution preserva-

tion mechanisms: their preferred RGB resolution depends

both on the desired privacy level and robot proximity during

navigation. Based on these findings, we further derive a user-

configurable distance-to-resolution privacy policy for privacy-

preserving robot visual navigation.