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A 6DoF VR Dataset of 3D virtualWorld for Privacy-Preserving Approach and Utility-Privacy Tradeoff
Conference paper

A 6DoF VR Dataset of 3D virtualWorld for Privacy-Preserving Approach and Utility-Privacy Tradeoff

Yu-Szu Wei, Xing Wei, Shin-Yi Zheng, Cheng-Hsin Hsu and Chenyang Yang
MMSys 2023 - Proceedings of the 14th ACM Multimedia Systems Conference, pp.444-450
06/2023

Abstract

attack Dataset defense HMD privacy virtual reality Computer Graphics and Computer-Aided Design Human-Computer Interaction Software
Virtual Reality (VR) applications offer an immersive user experience at the expense of privacy leakage caused by inevitably streaming various new types of user data. While some privacy-preserving approaches have been proposed for protecting one type of data, how to design and evaluate approaches for multiple types of user data are still open. On the other hand, preserving privacy will degrade the quality of experience of VR applications or say the utility of user data. How to achieve efficient utility-privacy tradeoff with multiple types of data is also open. Both call for a dataset that contains multiple types of user data and personal attributes of users as ground-Truth values. In this paper, we collect a 6 degree-of-freedom VR dataset of 3D virtual worlds for the investigation of privacy-preserving approaches and utility-privacy tradeoff.

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