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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 |
ISSN | 1553-572X |
发表状态 | 已发表 |
DOI | 10.1109/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 |
EISSN | 2577-1647 |
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. |
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