基于单目SLAM的多人AR定位系统,解决虚拟物体遮挡问题
A Monocular SLAM-based Multi-User Positioning System with Image Occlusion in Augmented Reality
- 用ORB-SLAM2与单目摄像头实现多用户空间定位
- 通过深度图估计减少遮挡,使虚拟物体更自然
- 适合开发多人协同式AR应用的开发者
近年来,随着增强现实(AR)技术的快速发展,对多人协作体验的需求日益增长。与单用户场景不同,确保每位用户的精确定位,并保持多用户间位置与朝向的一致性与同步性是一项重大挑战。本文提出一种基于单目RGB图像的多用户定位系统,以Unity3D游戏引擎为开发平台,采用ORB-SLAM2实现用户定位,并在环境平面(如桌面)上放置共享虚拟物体,使每位用户都能获得合适的视角。这些虚拟物体作为多用户定位同步的参考点。定位信息通过中心服务器在各用户的AR设备间传递,从而以虚拟化身的形式呈现其他用户相对于虚拟物体的相对位置与移动。此外,我们利用深度学习技术从单张RGB图像估计深度图,以解决AR应用中的遮挡问题,使虚拟物体在场景中呈现更自然的效果。
原文摘要 · Abstract (English)
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.
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