动态拍摄下自动标定相机与投影仪，实现无固定设备的3D重建。
Neural shape reconstruction from multiple views with static pattern projection
- 用神经SDF结合体积微分渲染，实时自标定运动中的相机与投影仪
- 在合成与真实图像上均实现高精度3D重建，误差低于1.2mm
- 适合工业检测、逆向工程等需灵活扫描的场景
基于主动立体的三维形貌测量在工业检测、逆向工程和医疗系统中至关重要，因其能精确获取无纹理物体的形状。传统主动立体系统由相机与投影仪紧密固定组成，需精确标定，限制了系统灵活性。若能在扫描过程中自由移动相机与投影仪，将显著提升实用性。为此，本文提出一种方法：在相机与投影仪运动状态下捕获多视角图像，利用新型体素微分渲染技术驱动神经符号距离场（NeuralSDF）自动标定二者相对位姿，完成目标物体的三维重建。实验在合成与真实图像数据集上验证了该方法的有效性，实现了亚毫米级精度的3D重建。
原文摘要 · Abstract (English)
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.
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