Multiview Deformation for Dynamic Human Modeling
2023-10-19
会议录名称IECON 2023- 49TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY
ISSN1553-572X
发表状态已发表
DOI10.1109/IECON51785.2023.10311856
摘要We present a novel multi-view dynamic 3D human reconstruction technique based on model-based shape deformation. Our approach specifically targets at handling challenging cases such as textureless appearance, heavy occlusions, and depth order ambiguity that are problematic to stereo-based techniques. We propose to pose match and shape deform a human template model to avoid meshing the point cloud. To robustly match the template pose with image observations, we present a novel Graph Convolutional Networks (GCN) to gradually filter out erroneous views and impose appropriate weights on the optimal subset for recovering the 3D skeleton and warping the template shape. Next, We use the warped human template to guide the cross-view consistent semantic segmentation. We set out to deform the warped 3D model so that the silhouette of the deformed model best matches the target in respective views while maintaining semantic consistency. Comprehensive experiments on publicly available and our newly generated complex motion datasets show our approach significantly outperforms the state-of-the-art on sparse cameras, textureless regions (e.g., under black clothing), complex motions, etc. © 2023 IEEE.
关键词image processing 3D human modeling pose estimation semantic-driven shape deformation semantic labeling
会议名称49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023
会议地点Singapore, Singapore
会议日期16-19 Oct. 2023
URL查看原文
收录类别EI
语种英语
出版者IEEE Computer Society
EI入藏号20235015212399
EI主题词Semantics
EISSN2577-1647
EI分类号722 Computer Systems and Equipment ; 723 Computer Software, Data Handling and Applications ; 723.2 Data Processing and Image Processing ; 723.4 Artificial Intelligence ; 723.5 Computer Applications ; 741.2 Vision
原始文献类型Conference article (CA)
来源库IEEE
文献类型会议论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/347928
专题信息科学与技术学院
信息科学与技术学院_PI研究组_虞晶怡组
信息科学与技术学院_博士生
作者单位
1.School of Information Science and Technology, ShanghaiTech University, China;
2.University of Chinese Academy of Sciences, China;
3.Shanghai Institute of Microsystem and Information Technology, China
第一作者单位信息科学与技术学院
第一作者的第一单位信息科学与技术学院
推荐引用方式
GB/T 7714
Luo, Xi,Li, Yuwei,Yu, Jingyi. Multiview Deformation for Dynamic Human Modeling[C]:IEEE Computer Society,2023.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
个性服务
查看访问统计
谷歌学术
谷歌学术中相似的文章
[Luo, Xi]的文章
[Li, Yuwei]的文章
[Yu, Jingyi]的文章
百度学术
百度学术中相似的文章
[Luo, Xi]的文章
[Li, Yuwei]的文章
[Yu, Jingyi]的文章
必应学术
必应学术中相似的文章
[Luo, Xi]的文章
[Li, Yuwei]的文章
[Yu, Jingyi]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。