| id |
caadria2023_43 |
| authors |
Onishi, Ryo, Fukuda, Tomohiro and Yabuki, Nobuyoshi |
| year |
2023 |
| title |
Remote Sharing System for 3D Real Objects with Point Cloud Reconstruction Using Deep Learning Point Cloud Completion |
| source |
Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 381–390 |
| doi |
https://doi.org/10.52842/conf.caadria.2023.2.381
|
| summary |
Currently, teleconferencing via the internet is widely used in society. However, physical models such as design study models, which are often used in face-to-face meetings in the fields of architecture and urban design, cannot be shared in teleconferences where information is shared on a display. Telepresence is a technology for sharing 3D real objects at a distance that gives the sensation of sharing and experiencing the environment and objects at a remote location. As one such technology, a system has been developed in which the point cloud of a real object acquired by a camera is divided into objects by instance segmentation, and the divided point cloud is transmitted to the remote user, who can manipulate it on mixed reality. There is a problem of missing point clouds in areas not seen by the RGB-D camera, such as occlusion and the back of the camera. This research aims to develop a system that can remotely manipulate point clouds with more accurate geometry by using a point cloud completion technique based on deep learning to complement missing point clouds. This system is expected to contribute to smoother teleconferencing of remote participants. |
| keywords |
Remote meeting, Real-time sharing, Three-dimensional remote sharing, Mixed Reality, Point cloud completion |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (1,939,371 bytes) |
| references |
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