Space-Time Co-Segmentation of Articulated Point Cloud Sequences

作者：Yuan, Qing; Li, Guiqing; Xu, Kai; Chen, Xudong; Huang, Hui^*

来源：Computer Graphics Forum, 2016, 35(2): 419-429.

DOI：10.1111/cgf.12843

• 3D SHAPES
• MESH
• MOTION

Consistent segmentation is to the center of many applications based on dynamic geometric data. Directly segmenting a raw 3D point cloud sequence is a challenging task due to the low data quality and large inter-frame variation across the whole sequence. We propose a local-to-global approach to co-segment point cloud sequences of articulated objects into near-rigid moving parts. Our method starts from a per-frame point clustering, derived from a robust voting-based trajectory analysis. The local segments are then progressively propagated to the neighboring frames with a cut propagation operation, and further merged through all frames using a novel space-time segment grouping technqiue, leading to a globally consistent and compact segmentation of the entire articulated point cloud sequence. Such progressive propagating and merging, in both space and time dimensions, makes our co-segmentation algorithm especially robust in handling noise, occlusions and pose/view variations that are usually associated with raw scan data.

• 出版日期2016-5
• 单位中国人民解放军国防科学技术大学; 深圳大学; 华南理工大学