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AR HMD Guidance for Controlled Hand-Held 3D Acquisition

机译:适用于手持式3D采集的AR HMD指南

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Photogrammetry is a popular method of 3D reconstruction that uses conventional photos as input. This method can achieve high quality reconstructions so long as the scene is densely acquired from multiple views with sufficient overlap between nearby images. However, it is challenging for a human operator to know during acquisition if sufficient coverage has been achieved. Insufficient coverage of the scene can result in holes, missing regions, or even a complete failure of reconstruction. These errors require manually repairing the model or returning to the scene to acquire additional views, which is time-consuming and often infeasible. We present a novel approach to photogrammetric acquisition that uses an AR HMD to predict a set of covering views and to interactively guide an operator to capture imagery from each view. The operator wears an AR HMD and uses a handheld camera rig that is tracked relative to the AR HMD with a fiducial marker. The AR HMD tracks its pose relative to the environment and automatically generates a coarse geometric model of the scene, which our approach analyzes at runtime to generate a set of human-reachable acquisition views covering the scene with consistent camera-to-scene distance and image overlap. The generated view locations are rendered to the operator on the AR HMD. Interactive visual feedback informs the operator how to align the camera to assume each suggested pose. When the camera is in range, an image is automatically captured. In this way, a set of images suitable for 3D reconstruction can be captured in a matter of minutes. In a user study, participants who were novices at photogrammetry were tasked with acquiring a challenging and complex scene either without guidance or with our AR HMD based guidance. Participants using our guidance achieved improved reconstructions without cases of reconstruction failure as in the control condition. Our AR HMD based approach is self-contained, portable, and provides specific acquisition guidance tailored to the geometry of the scene being captured.
机译:摄影测量法是使用常规照片作为输入的一种流行的3D重建方法。只要从附近的图像之间有足够重叠的多个视图中密集地获取场景,该方法就可以实现高质量的重建。然而,对于人类操作员而言,在采集期间知道是否已经实现足够的覆盖范围是具有挑战性的。场景的覆盖范围不足可能会导致出现孔洞,缺少区域,甚至导致重建完全失败。这些错误需要手动修复模型或返回场景以获取其他视图,这既费时又不可行。我们提出了一种新的摄影测量方法,该方法使用AR HMD来预测一组覆盖视图并交互式地指导操作员从每个视图捕获图像。操作员佩戴AR HMD,并使用手持式摄影机,并使用基准标记相对于AR HMD进行跟踪。 AR HMD会跟踪其相对于环境的姿态,并自动生成场景的粗略几何模型,我们的方法会在运行时对其进行分析,以生成一组可人类到达的采集视图,以一致的相机到场景距离和图像覆盖场景交叠。生成的视图位置在AR HMD上呈现给操作员。交互式视觉反馈可告知操作员如何对准摄像机以采取每个建议的姿势。当照相机在范围内时,将自动捕获图像。通过这种方式,可以在几分钟内捕获适合3D重建的一组图像。在一项用户研究中,摄影测量新手的参与者需要在没有指导的情况下或在我们基于AR HMD的指导下获得具有挑战性和复杂的场景。参加者在我们的指导下获得了更好的重建效果,而没有在控制条件下出现重建失败的情况。我们基于AR HMD的方法是独立的,可移植的,并提供了针对所捕获场景的几何形状量身定制的特定采集指导。

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