Systems that give control of a mobile robot to a remote user raise privacyconcerns about what the remote user can see and do through the robot. We aim topreserve some of that privacy by manipulating the video data that the remoteuser sees. Through two user studies, we explore the effectiveness of differentvideo manipulation techniques at providing different types of privacy. Wesimultaneously examine task performance in the presence of privacy protection.In the first study, participants were asked to watch a video captured by arobot exploring an office environment and to complete a series of observationaltasks under differing video manipulation conditions. Our results show thatusing manipulations of the video stream can lead to fewer privacy violationsfor different privacy types. Through a second user study, it was demonstratedthat these privacy-protecting techniques were effective without diminishing thetask performance of the remote user.
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