标题:Dynamic 3D facial expression modeling using Laplacian smooth and multi-scale mesh matching
作者:Chi, Jing; Tu, Changhe; Zhang, Caiming
通讯作者:Chi, J
作者机构:[Chi, Jing; Zhang, Caiming] Shandong Univ Finance & Econ, Dept Comp Sci & Technol, Jinan, Peoples R China.; [Chi, Jing; Tu, Changhe; Zhang, Caiming] 更多
会议名称:31st CGI conference
会议日期:JUN 10-13, 2014
来源:VISUAL COMPUTER
出版年:2014
卷:30
期:6-8
页码:649-659
DOI:10.1007/s00371-014-0960-3
关键词:Expression modeling; Laplacian smooth; Mesh matching; Point clouds
摘要:We propose a novel algorithm for the high-resolution modeling of dynamic 3D facial expressions from a sequence of unstructured face point clouds captured at video rate. The algorithm can reconstruct not only the global facial deformations caused by muscular movements, but also the expressional details generated by local skin deformations. Our algorithm consists of two parts: Extraction of expressional details and Reconstruction of expressions. In the extraction part, we extract the subtle expressional details such as wrinkles and folds from each point cloud with Laplacian smooth operator. In the reconstruction part, we use a multi-scale deformable mesh model to match each point cloud to reconstruct time-varying expressions. In each matching, we first use the low-scale mesh to match the global deformations of point cloud obtained after filtering out the expressional details, and then use the high-scale mesh to match the extracted expressional details. Comparing to many existing non-rigid ICP-based algorithms that match directly the mesh model to the entire point cloud, our algorithm overcomes the probable large errors occurred where the local sharp deformations are matched since it extracts the expressional details for separate matching, therefore, our algorithm can produce a high-resolution dynamic model reflecting time-varying expressions. Additionally, utilization of multi-scale mesh model makes our algorithm achieve high speed because it decreases iterative optimizations in matching. Experiments demonstrate the efficiency of our algorithm.
收录类别:CPCI-S;EI;SCOPUS;SCIE
WOS核心被引频次:3
Scopus被引频次:4
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902201589&doi=10.1007%2fs00371-014-0960-3&partnerID=40&md5=96d384e62c514abd6b01cf8d5f01cb61
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