摘要
针对三维人体模型语义获取和对称区分的难题,提出一种自动的、左右可区分的三维人体模型语义分割方法.对于输入的人体模型,首先采用模板嵌入的方法提取其左右可区分的、具有语义信息的运动骨架;然后基于运动骨架确定人体模型的分割块数量,并提取各个分割块对应的关键点;再以关键点为边界约束计算模型的调和场,获取分割线的候选集;最后以关键点为聚类中心对模型进行谱聚类,利用聚类结果引导分割线的筛选,确定其中准确的分割线.该方法使骨架的语义信息可直接传递至三维人体模型的分割块,且借助骨架的结构可以控制分割块的数量.在SCAPE数据库、MPI-FAUST数据库和普林斯顿分割数据集上的结果表明,对不同形状和姿态的三维人体模型,该方法均能自动、鲁棒地实现对称可区分的语义分割.
An automatic segmentation method for a 3 D human model is proposed for the symmetry-aware semantic segmentation.Firstly,a symmetry-aware kinematic skeleton is extracted from the input human body model via template skeleton embedding.Secondly,the number of the segments is determined by the kinematic skeleton;some key points corresponding to the segments are extracted meanwhile.Thirdly,while taking the key points as the boundary constraints,the harmonic fields are constructed to obtain a set of isolines as the potential cutting boundaries.Finally,the key points are taken as the clustering centers to conduct a spectral clustering operation,which guides the selections of the cutting boundaries.In this way,the semantic information in the kinematic skeleton can be directly transferred to the segments,and the number of segments can be controlled by the structure of the kinematic skeleton.Results on the SCAPE dataset,the MPI-FAUST dataset and the Princeton Segmentation Benchmark show that the proposed method can automatically achieve symmetry-aware semantic segmentation,and is robust to the shape and the pose of the human body model.
作者
罗闪
张栖桐
冯结青
Luo Shan;Zhang Qitong;Feng Jieqing(State Key Laboratory of CAD&CG,Zhejiang University,Hangzhou 310058)
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2021年第7期1064-1072,共9页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(61732015,61472349)
浙江省重点研发计划(2018C01090)。
关键词
三维人体模型
对称可区分
语义分割
调和场
谱聚类
3D human body model
symmetry-aware
semantic segmentation
harmonic field
spectral clustering
作者简介
罗闪(1993-),女,博士研究生,CCF会员,主要研究方向为三维模型的数字几何处理;张栖桐(1996-),女,博士研究生,主要研究方向为计算机视觉;通讯作者:冯结青(1970-),男,博士,教授,博士生导师,CCF杰出会员,主要研究方向为计算机图形学、计算机视觉、光热太阳能仿真等,jqfeng@cad.zju.edu.cn。
