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作 者:普骏程 刘骊[1,2] 付晓东 刘利军[1,2] 黄青松 Pu Juncheng;Liu Li;Fu Xiaodong;Liu Lijun;Huang Qingsong(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500;Computer Technology Application Key Laboratory of Yunnan Province,Kunming 650500)
机构地区:[1]昆明理工大学信息工程与自动化学院,昆明650500 [2]云南省计算机技术应用重点实验室,昆明650500
出 处:《计算机辅助设计与图形学学报》2022年第3期352-363,共12页Journal of Computer-Aided Design & Computer Graphics
基 金:国家自然科学基金(61862036,61962030,81860318);云南省中青年学术和技术带头人后备人才培养计划(201905C160046)。
摘 要:针对三维人体重建中服装视觉信息表示模糊的问题,提出一种多阶段优化的三维人体重建方法.首先对输入的人体图像进行预处理,分别提取其语义特征、明暗特征和高频特征;然后基于局部深度特征构建有向距离场,隐式表征三维人体的几何形状;再构建着装层次表示模块,通过定义着装层次损失函数感知服装语义上下文信息,并优化有向距离场,生成粗糙的三维人体模型;最后结合明暗特征和高频特征捕获服装褶皱细节,并在UV空间内定位褶皱位置,优化生成精细的三维人体模型.在BUFF数据集上的实验结果表明,所提方法的法线L2误差和倒角距离误差分别为0.13和1.30,较已有方法降低了13%和2%,能够提高三维人体重建的精度,生成具有服装款式、着装层次和褶皱细节的三维人体模型.To address the problem of fuzzy representation of clothing visual information in three-dimensional human reconstruction,a multi-stage based optimization method is proposed.Firstly,semantic features,shading features and high-frequency features are extracted from input images in preprocess.Secondly,the signed distance field is constructed based on the local depth features to implicitly represent the shape of clothed human.Then,to optimize the signed distance field and generate the rough three-dimensional human model,the dress hierarchy module is constructed,and the clothing semantic context is perceived by defining the dress hierarchy loss function.Finally,combining the shading features and high-frequency features to capture the details of wrinkles in the UV space,and an accurate three-dimensional human model is generated.The experimental results on BUFF dataset show that the normal L2 error and the chamfer distance error are 0.13 and 1.30 respectively,which reduce by 13%and 2%.The proposed method can improve the accuracy of three-dimensional human reconstruction,which generates three-dimensional human model with clothing style,dress hierarchy and wrinkles.
关 键 词:三维人体重建 服装视觉信息表示 局部深度特征 有向距离场 上下文信息
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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