IEEE Trans Cybern. 2017 Mar;47(3):695-708. doi: 10.1109/TCYB.2016.2524406. Epub 2016 Feb 23.
Full human body shape scans provide valuable data for a variety of applications including anthropometric surveying, clothing design, human-factors engineering, health, and entertainment. However, the high price, large volume, and difficulty of operating professional 3-D scanners preclude their use in home entertainment. Recently, portable low-cost red green blue-depth cameras such as the Kinect have become popular for computer vision tasks. However, the infrared mechanism of this type of camera leads to noisy and incomplete depth images. We construct a stereo full-body scanning environment composed of multiple depth cameras and propose a novel registration algorithm. Our algorithm determines a segment constrained correspondence for two neighboring views, integrating them using rigid transformation. Furthermore, it aligns all of the views based on uniform error distribution. The generated 3-D mesh model is typically sparse, noisy, and even with holes, which makes it lose surface details. To address this, we introduce a geometric and topological fitting prior in the form of a professionally designed high-resolution template model. We formulate a template deformation optimization problem to fit the high-resolution model to the low-quality scan. Its solution overcomes the obstacles posed by different poses, varying body details, and surface noise. The entire process is free of body and template markers, fully automatic, and achieves satisfactory reconstruction results.
全身形状扫描为各种应用提供了有价值的数据，包括人体测量调查、服装设计、人体工程学、健康和娱乐。然而，专业的 3D 扫描仪价格高、体积大、操作难度大，不适合家庭娱乐使用。最近，便携式低成本红绿蓝深度相机（如 Kinect）已成为计算机视觉任务的热门选择。然而，这种类型的相机的红外机制会导致深度图像嘈杂和不完整。我们构建了一个由多个深度相机组成的立体全身扫描环境，并提出了一种新的注册算法。我们的算法为两个相邻视图确定了分段约束对应关系，使用刚性变换对其进行集成。此外，它还基于均匀误差分布对齐所有视图。生成的 3D 网格模型通常是稀疏的、嘈杂的，甚至有空洞，这使得它失去了表面细节。为了解决这个问题，我们以专业设计的高分辨率模板模型的形式引入了几何和拓扑拟合先验。我们制定了一个模板变形优化问题，以将高分辨率模型拟合到低质量的扫描中。其解决方案克服了不同姿势、不同身体细节和表面噪声带来的障碍。整个过程无需身体和模板标记，完全自动化，并实现了令人满意的重建结果。
