.png){kind=icon}
返回
Sweep-based human deformation
.png){kind=icon}
PRE
AI
DOI：10.1007/s00371-005-0343-x.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We present a sweep-based approach to human body modeling and deformation. A rigid 3D human model, given as a polygonal mesh, is approximated with control sweep surfaces. The vertices on the mesh are bound to nearby sweep surfaces and then follow the deformation of the sweep surfaces as the model bends and twists its arms, legs, spine and neck. Anatomical features including bone-protrusion, muscle-bulge, and skin-folding are supported by a GPU-based collision detection procedure. The volumes of arms, legs, and torso are kept constant by a simple control using a volume integral formula for sweep surfaces. We demonstrate the effectiveness of this sweep-based human deformation in several test animation clips.
Keyword:
human modeling and deformation
sweep surface
vertex binding
shape blending
anatomical features
volume preservation
期刊
IF:
2.9
论文数:
4.6K
被引数:
6.5K
机构
暂无机构信息
引用论文
Analyzing Aircraft Controllability After Engine Failure During Takeoff in Adverse Weather Conditions
OAAI
OAAI分享收藏Strength training to improve walking after stroke: how physiotherapist, patient and workplace factors influence exercise prescription卒中后步行能力改善的增强训练：物理治疗师、患者及工作场所因素如何影响运动处方
PREAI
分享收藏A 3D convolutional neural network to classify subjects as Alzheimer's disease, frontotemporal dementia or healthy controls using brain 18F-FDG PET.png)
NeuroImageOAAI
NeuroImageIF0
OAAI分享收藏分享收藏分享收藏
查看更多内容