王胜法

个人信息Personal Information

副教授

博士生导师

硕士生导师

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:软件学院、国际信息与软件学院

学科:软件工程. 计算机应用技术. 计算数学

办公地点:信息楼317

联系方式:0411-62274427 250066715@qq.com

电子邮箱:sfwang@dlut.edu.cn

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An adapted parameterization for smooth geometry images

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论文类型:会议论文

发表时间:2013-11-16

收录刊物:EI、CPCI-S、Scopus

页面范围:156-163

关键字:geometry images; mesh parameterization; approximation error; local linear error

摘要:Geometry images are important representations of 3D geometry models. Smooth geometry images contributes to low approximation error and high image compressibility. We present an adapted parameterization method to generate a smooth geometry image. It is quite challenging to directly modify the parameter domain to smooth geometry images. Our novel idea is that we use an indirect way to construct a resulting parameter domain according to the desired geometry image. We first move image pixels according to the current parameter domain to decrease the local linear error. Then we formulate a relationship between the moved image pixels and the current parameter domain. Finally, we use the relationship to update the parameter domain by restituting the image pixels to their original positions. The process will continue until the local linear error is less than a given threshold or the number of iterations is larger than a given threshold. Experimental results illustrate that geometry images generated by our method have low linear errors and low approximation errors under different sampling resolutions.