计算机工程Issue(9)：240-244,5.DOI:10.3969/j.issn.1000-3428.2013.09.054
基于分块主成分分析的人体运动合成
Human Motion Synthesis Based on Block Principal Component Analysis
摘要
Abstract
Human motion analysis based on traditional dimensional reduction methods often overstresses topology preservation and reconstruction precision which results in incomprehensible low-dimensional subspaces. To solve this problem, this paper proposes a Block Principal Component Analysis(BPCA) based method to analyze motion capture data and further synthesize human motions interactively. By applying BPCA to different body parts, low-dimensional motion parameters which are semantically meaningful can be obtained. Taking jumping motion as the example, experimental results show that by intuitively adjusting these motion parameters, desired new motions can be generated in real-time.关键词
三维人体动画/运动捕获数据/运动合成/主成分分析/分块主成分分析/动态时间弯曲Key words
3D human animation/motion capture data/motion synthesis/Principal Component Analysis(PCA)/block PCA/dynamic time warping分类
信息技术与安全科学引用本文复制引用
李妙洋,蓝荣祎,孙怀江..基于分块主成分分析的人体运动合成[J].计算机工程,2013,(9):240-244,5.基金项目
南京理工大学自主科研专项计划基金资助项目(2011YBXM79)；江苏省2011年度普通高校研究生科研创新计划基金资助项目(CXLX11_0260) （2011YBXM79）
