Journal · 2024

Understanding Privacy Awareness in Immersive Spatial Sharing System

Tomokazu Matsui , Shigetomo Sakuma , Yuki Mishima , Hirohiko Suwa , Keiichi Yasumoto , Tatsuya Amano , Hirozumi Yamaguchi

Sensors and Materials, Volume 36, Number 10(3) (2024), pp. 4567-4583

DOI: 10.18494/SAM5213

Abstract

With the advancement of point cloud collection technology and high-performance computing, immersive remote spatial sharing systems that enhance caregiving and family interaction are highly anticipated.In particular, advanced spatial sharing systems are being developed to scan and merge each other's spaces into a virtual environment.However, this new form of interaction may raise privacy concerns distinct from those associated with traditional telephone or video conferencing.In this study, we investigated the privacy concerns arising from highly immersive spatial sharing systems.We developed a spatial sharing system consisting of multiple depth cameras and servers designed for use in two or more remote locations.Each location's surrounding environments and objects are captured and represented as point clouds, then mapped into a shared virtual space.Thirty-nine participants attended an experience session on the spatial sharing system and responded to a questionnaire.The survey collected information on privacy awareness during the use of the spatial sharing system, the quality of the system's equipment and interactions, and some basic user attributes.Additionally, it inquired how users' awareness changes when some parts of the space related to subjective privacy are modified.Furthermore, data was segmented into clusters based on age group and gender, and statistical tests were conducted between two groups within each cluster.The results showed several statistically significant differences, including differences in privacy awareness and the usefulness of the proposed spatial sharing system.

Research Note

Advances in point cloud capture and in computing power have brought immersive spatial sharing systems within reach, in which distant places are merged inside a virtual environment so that participants can behave as if they shared a room. Applications in caregiving and family interaction are anticipated.

This form of interaction differs in kind from a telephone call or a video conference. In a video call the user controls what is visible by pointing the camera, whereas spatial sharing reads the room itself, so an untidy shelf, the spines of books, or the objects that reveal someone's tastes are transmitted without being chosen. Privacy concerns arise in a new form.

The system built for this study consists of multiple depth cameras and servers and is designed for use across two or more remote locations. The surroundings and objects at each location are captured as point clouds and mapped into a shared virtual space. Thirty-nine participants attended an experience session and answered a questionnaire covering privacy awareness during use, the quality of the equipment and the interaction, and basic user attributes. They were also asked how their awareness changed when parts of the space they regarded as private were modified.

Segmenting responses into clusters by age group and gender and applying statistical tests between two groups within each cluster revealed several statistically significant differences, in privacy awareness and in the perceived usefulness of the system alike. What people find sensitive is evidently not uniform.

新生活様式におけるコミュニティ形成のためのサイバーフィジカル空間共有基盤

新生活様式におけるコミュニティ形成のためのサイバーフィジカル空間共有基盤

National Institute of Information and Communications Technology (NICT) 高度通信・放送研究開発委託研究
ウイルス等感染症対策に資する情報通信技術の研究開発 課題C: アフターコロナ社会を形成するICT

Environment-Aware Distributed Scheduling for Emergency LoRa Networks

Yuto Inaba, Tatsuya Amano, Akihito Hiromori, Hirozumi Yamaguchi

2026 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), SPT-IoT 2026, pp. 1366–1371

DOI 10.1109/PerComWorkshops68308.2026.11585469

Disaster CommunicationLoRa +4

A Lightweight Vision-Language Model for Disaster Image Summarization

Hibiki Yoshizaki, Akira Uchiyama, Akihito Hiromori, Mineo Takai, Hirozumi Yamaguchi

2026 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), PerconAI 2026, pp. 1203–1208

DOI 10.1109/PerComWorkshops68308.2026.11585419

Semantic CommunicationDisaster Response +4

Physics-Integrated Deep Learning for Urban Landslide Prediction

Ren Ozeki, Hamada Rizk, Hirozumi Yamaguchi

2026 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), URBSENSE 2026, pp. 1094–1099

DOI 10.1109/PerComWorkshops68308.2026.11585337

Landslide PredictionPhysics-Integrated Learning +3

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Tatsuya Amano, Akihito Hiromori, Hirozumi Yamaguchi, Sumio Morioka

2026 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), PerVehicle , pp. 230–235

DOI 10.1109/PerComWorkshops68308.2026.11585321

Satellite Formation FlyingDistributed Simulation +4

Ray-Tracing-Driven Pattern-Based Vehicle Recognition in ISAC Radar

Heetae Jin, Akira Uchiyama

2026 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), PerRad 2026, pp. 328–333

DOI 10.1109/PerComWorkshops68308.2026.11585327

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A Questionnaire-Only Counterfactual Machine Learning Approach to Assess the Spatial Impact of Green Mobility Vehicles in Urban Parks

Rami Naeem, Srikant Manas, Tatsuya Amano, Hirozumi Yamaguchi

ICDCN 2026 Workshop: IWNDSC2026

DOI 10.1145/3737611.3776620