CAJ | 학술논문

为解决现有运动合成方法中控制方式过于复杂的问题,提出一种模板化的运动合成模型,旨在降低运动合成技术的应用门槛。利用稀疏主成分分析(Sparse principal component analysis, SPCA)、Group lasso 和Exclusive group lasso 对人体运动进行建模,使其对应的每一个低维参数只依赖于少数几个人体关节,构成人体运动的一个内在自由度(Degree of freedom, DOF),并具有直观语义；同时,每个关节被尽量少的低维参数所控制,以减少低维参数对彼此所控制的自由度的交叉影响。实验表明,通过直观地修改低维参数,就能够实时地控制每个参数对应的摆臂幅度、踢腿高度、跳跃距离等运动属性。这种“模板学习、模板定制”的两步方法,有效地降低了运动合成控制的复杂度,即便非专业人员也可以用其进行艺术创作。
위해결현유운동합성방법중공제방식과우복잡적문제,제출일충모판화적운동합성모형,지재강저운동합성기술적응용문함。이용희소주성분분석(Sparse principal component analysis, SPCA)、Group lasso 화Exclusive group lasso 대인체운동진행건모,사기대응적매일개저유삼수지의뢰우소수궤개인체관절,구성인체운동적일개내재자유도(Degree of freedom, DOF),병구유직관어의；동시,매개관절피진량소적저유삼수소공제,이감소저유삼수대피차소공제적자유도적교차영향。실험표명,통과직관지수개저유삼수,취능구실시지공제매개삼수대응적파비폭도、척퇴고도、도약거리등운동속성。저충“모판학습、모판정제”적량보방법,유효지강저료운동합성공제적복잡도,즉편비전업인원야가이용기진행예술창작。
Since the existing approaches to control human motion synthesis are too complicated, we propose a templated motion synthesis model to reduce the di?culty of using motion synthetic technology. We use sparse principal component analysis (SPCA), group lasso and exclusive group lasso to model human motions so that each low-dimensional parameter depends on a few human joints which form an intrinsic degree of freedom (DOF) with intuitive meanings. Meanwhile, our approach makes each joint controlled by as few low-dimensional parameters as possible to reduce the interferences between different DOFs. Our experiments demonstrate that users can control the motion features like amplitude of swing arm, kick height and jump distance by modifying the low-dimensional parameters intuitively in real time. This two-step approach of “template learning and template customization” can effectively reduce the complexity of synthesis control, and allows inexperienced users to create a realistic human animation quickly and easily.