标题： 具有静态图案投影的多视图神经形状重建 显示英文标题

标题： Neural shape reconstruction from multiple views with static pattern projection

摘要： 基于主动立体视觉的三维形状测量对于工业检测、逆向工程和医疗系统等多种用途至关重要，因为它能够准确获取无纹理物体的形状。 主动立体系统通常由一个相机和一个图案投影仪组成，它们被牢固地固定在一起，并且需要精确校准相机和投影仪之间的关系，这反过来降低了系统的可用性。 如果在形状扫描过程中相机和投影仪可以自由移动，则会极大地提高系统的可用性。 为了实现这一点，我们提出了一种技术，通过捕获多张图像并在相机和投影仪运动的同时自动校准它们的相对姿态（使用基于神经符号距离场 (NeuralSDF) 的新型体积微分渲染技术）来恢复目标物体的形状。 在实验中，通过使用合成图像和真实图像进行三维重建来评估所提出的方法。 显示英文摘要

摘要： Active-stereo-based 3D shape measurement is crucial for various purposes, such as industrial inspection, reverse engineering, and medical systems, due to its strong ability to accurately acquire the shape of textureless objects. Active stereo systems typically consist of a camera and a pattern projector, tightly fixed to each other, and precise calibration between a camera and a projector is required, which in turn decreases the usability of the system. If a camera and a projector can be freely moved during shape scanning process, it will drastically increase the convenience of the usability of the system. To realize it, we propose a technique to recover the shape of the target object by capturing multiple images while both the camera and the projector are in motion, and their relative poses are auto-calibrated by our neural signed-distance-field (NeuralSDF) using novel volumetric differential rendering technique. In the experiment, the proposed method is evaluated by performing 3D reconstruction using both synthetic and real images.