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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2411.10940 |
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| _version_ | 1866929594762788864 |
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| author | Lien, Wei-Hsiang Chandra, Benedictus Kent Fischer, Robin Tang, Ya-Hui Wang, Shiann-Jang Hsu, Wei-En Fu, Li-Chen |
| author_facet | Lien, Wei-Hsiang Chandra, Benedictus Kent Fischer, Robin Tang, Ya-Hui Wang, Shiann-Jang Hsu, Wei-En Fu, Li-Chen |
| contents | In recent years, with the rapid development of augmented reality (AR) technology, there is an increasing demand for multi-user collaborative experiences. Unlike for single-user experiences, ensuring the spatial localization of every user and maintaining synchronization and consistency of positioning and orientation across multiple users is a significant challenge. In this paper, we propose a multi-user localization system based on ORB-SLAM2 using monocular RGB images as a development platform based on the Unity 3D game engine. This system not only performs user localization but also places a common virtual object on a planar surface (such as table) in the environment so that every user holds a proper perspective view of the object. These generated virtual objects serve as reference points for multi-user position synchronization. The positioning information is passed among every user's AR devices via a central server, based on which the relative position and movement of other users in the space of a specific user are presented via virtual avatars all with respect to these virtual objects. In addition, we use deep learning techniques to estimate the depth map of an image from a single RGB image to solve occlusion problems in AR applications, making virtual objects appear more natural in AR scenes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_10940 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Monocular SLAM-based Multi-User Positioning System with Image Occlusion in Augmented Reality Lien, Wei-Hsiang Chandra, Benedictus Kent Fischer, Robin Tang, Ya-Hui Wang, Shiann-Jang Hsu, Wei-En Fu, Li-Chen Human-Computer Interaction Computer Vision and Pattern Recognition In recent years, with the rapid development of augmented reality (AR) technology, there is an increasing demand for multi-user collaborative experiences. Unlike for single-user experiences, ensuring the spatial localization of every user and maintaining synchronization and consistency of positioning and orientation across multiple users is a significant challenge. In this paper, we propose a multi-user localization system based on ORB-SLAM2 using monocular RGB images as a development platform based on the Unity 3D game engine. This system not only performs user localization but also places a common virtual object on a planar surface (such as table) in the environment so that every user holds a proper perspective view of the object. These generated virtual objects serve as reference points for multi-user position synchronization. The positioning information is passed among every user's AR devices via a central server, based on which the relative position and movement of other users in the space of a specific user are presented via virtual avatars all with respect to these virtual objects. In addition, we use deep learning techniques to estimate the depth map of an image from a single RGB image to solve occlusion problems in AR applications, making virtual objects appear more natural in AR scenes. |
| title | A Monocular SLAM-based Multi-User Positioning System with Image Occlusion in Augmented Reality |
| topic | Human-Computer Interaction Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2411.10940 |