Kinect扫描数据驱动的几何建模方法

Kinect-Based Data-Driven 3D Modeling

针对Kinect设备单视角扫描所得不完整点云数据,提出了一种快速三维建模方法.利用互联网上丰富的已有同类三维模型为资源进行三维建模,建模过程主要包括3个阶段:1)通过三维模型库的语义部件标注对所需建模的点云数据和图像数据进行结构分析,获得相应的部件级分割结果;2)利用点云和图像分割所得的部件级信息在三维模型库中搜索与其匹配的各部件;3)对搜索得到的部件进行组合,以获得与扫描模型相似的最终模型.实验结果表明,该方法能够快速、高效地完成对Kinect设备扫描所得的残缺点云数据的模型重建.

This paper presents a fast modeling method based on the highly noisy and incomplete scanned data from Kinect in a single view .We take full advantage of the abundant models of the same semantic class on the Internet to build a heuristic model based on the 3D point clouds and the corresponding RGB images .Our method includes three major phases ：Firstly ,we analyze the structure of the 3D point clouds and the RGB images based on the semantic segmentation of the candidate model to label the components of the scanned target ;secondly ,we search for candidate parts for the labeled parts in the target to get matched component information ;lastly ,we assemble the candidate parts to create the final 3D model .We demonstrate the efficiency and speed of our method in building models based on incomplete point clouds data from Kinect .