Cloud-based collaborative 3D reconstruction using smartphones

F. Poiesi, Alex Locher, P. Chippendale, E. Nocerino, Fabio Remondino, L. Gool
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引用次数: 30

Abstract

This article presents a pipeline that enables multiple users to collaboratively acquire images with monocular smartphones and derive a 3D point cloud using a remote reconstruction server. A set of key images are automatically selected from each smartphone's camera video feed as multiple users record different viewpoints of an object, concurrently or at different time instants. Selected images are automatically processed and registered with an incremental Structure from Motion (SfM) algorithm in order to create a 3D model. Our incremental SfM approach enables on-the-fly feedback to the user to be generated about current reconstruction progress. Feedback is provided in the form of a preview window showing the current 3D point cloud, enabling users to see if parts of a surveyed scene need further attention/coverage whilst they are still in situ. We evaluate our 3D reconstruction pipeline by performing experiments in uncontrolled and unconstrained real-world scenarios. Datasets are publicly available.
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使用智能手机进行基于云的协同3D重建
本文介绍了一个管道,使多个用户能够通过单目智能手机协作获取图像,并使用远程重建服务器派生3D点云。当多个用户同时或在不同时刻记录一个物体的不同视角时,一组关键图像会自动从每个智能手机的摄像头视频馈送中选择出来。选择的图像自动处理和注册与增量结构从运动(SfM)算法,以创建一个3D模型。我们的增量SfM方法可以实时反馈给用户当前的重建进度。反馈以预览窗口的形式提供,显示当前的3D点云,使用户能够看到被调查场景的某些部分是否需要进一步关注/覆盖,而它们仍然在原位。我们通过在不受控制和不受约束的现实世界场景中进行实验来评估我们的3D重建管道。数据集是公开的。
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