摘要
为降低服装三维模型的重建难度,提升三维服装模型的重建效率,提出一种基于多视角单目的服装三维重建方法,该方法首先获取服装图像序列,然后对服装图像序列进行实例化分割获得含服装部分的轮廓信息,使用SIFT算法提取每张图像的特征点和匹配对,加入双重约束去除误差匹配对。然后进行稀疏点云以及稠密点云的重建,最后使用泊松重建还原服装表面细节。结果表明:在多视觉单目服装三维重建过程加入实例分割和双重约束后可以将特征的匹配率提升至88.3%,三维重建的速度较传统方法提升了22%。该方法在服装三维模型重建的过程中也能较好还原服装表面细节。
In order to reduce the difficulty of 3 D garment model reconstruction and improve the efficiency of 3 D garment model reconstruction,a 3 D reconstruction method based on multi-view monocular garment is presented.In this method,the garment image sequence is firstly obtained,and then the contour information of garment is obtained by instantiating and segmenting the garment image sequence.The feature points and matching pairs of each image are extracted by using SIFT algorithm and error matching pairs are eliminated by adding dual constraints.Then,sparse point cloud and dense point cloud are reconstructed,and finally the surface details of the garment are restored by Poisson reconstruction.The results show that after adding instance segmentation and dual constraints to the 3 D reconstruction process of multi-view monocular garment,the matching rate of features can increase to 88.3%,and the speed of 3 D reconstruction can increase by 22%compared with the traditional method.This method can also restore the surface details of the garment properly in the process of 3 D model reconstruction.
作者
胡新荣
曾潇
刘军平
彭涛
何儒汉
陈常念
HU Xinrong;ZENG xiao;LIU Junping;PENG Tao;HE Ruhan;CHEN Changnian(School of Computer Science and Artificial Intelligence,Wuhan Textile University,Wuhan 430200,China)
出处
《现代纺织技术》
北大核心
2021年第6期84-90,共7页
Advanced Textile Technology
基金
国家自然科学基金项目(61103085)
湖北省高校优秀中青年科技创新团队计划项目(T201807)。
关键词
服装重建
实例分割
特征点检测
特征点匹配
点云
garment reconstruction
instance segmentation
feature point detection
feature point matching
point cloud
作者简介
胡新荣(1974-),女,武汉人,教授,博士,主要从事图形图像处理方面的研究。
