3D Human Body Inpainting using Intrinsic Statistical Shape Models

被引：0

作者：

Korban, Matthew ^{[1
]}

Li, Xin ^{[1
]}

Miao, Kehua ^{[2
]}

Zhu, Yimin ^{[3
]}

机构：

[1] Louisiana State Univ, Div Comp Engn, Baton Rouge, LA 70803 USA

[2] Xiamen Univ, Dept Automat, Xiamen, Peoples R China

[3] Louisiana State Univ, Dept Construct Management, Baton Rouge, LA 70803 USA

来源：

14TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND EDUCATION (ICCSE 2019) | 2019年

关键词：

Statistical Shape Model; Human Body Inpainting; Laplacian Coordinates;

D O I：

10.1109/iccse.2019.8845520

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper presents an algorithm for inpainting 3D human body geometry. We built a Statistical Shape Model (SSM) based on the intrinsic Laplacian Coordinates (LC) to tackle the pose variation of human bodies, which is a common challenging issue in 3D human body modeling and shape analysis. We evaluate our inpainting algorithm using synthesized damages on complete human body scans, and with the groundtruth we measure the normalized reconstruction error quantitatively. Our experiments demonstrate the effectiveness of this LC-based SSM in human body inpainting.

引用

页码：1105 / 1110

页数：6

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