服装动画中人体运动与服装变形的相关性学习
发布时间：2018-11-15 08:39
【摘要】：针对服装动画中人体运动与服装变形的关系,首先对服装动画中人体运动特征和服装变形特征进行定义和提取;其次建立多套服装在多种人体运动下的高精度服装动画实例数据,并基于4种机器学习模型从实例中学习二者之间的关系.对不同学习模型进行实验的结果表明,由于服装动画中人体运动与服装变形之间存在较强的相关性,因此利用人体运动可以较为准确地预测服装的变形分布;相比BP神经网络,广义回归神经网络和支持向量机等方法,随机森林模型可以更有效地获取人体运动与服装变形的关系,最终误差可控制在理想范围内.
[Abstract]:In view of the relationship between human body movement and garment deformation in clothing animation, the characteristics of human body motion and clothing deformation in clothing animation are defined and extracted firstly. Secondly, the high precision clothing animation case data of multiple sets of clothing under various human motion are established, and the relationship between them is learned from the examples based on four machine learning models. The experimental results of different learning models show that because there is a strong correlation between human body motion and garment deformation in clothing animation, the deformation distribution of clothing can be predicted more accurately by using human body motion. Compared with BP neural network, generalized regression neural network and support vector machine, the stochastic forest model can obtain the relationship between human body motion and garment deformation more effectively, and the final error can be controlled within an ideal range.
【作者单位】： 华北电力大学控制与计算机工程学院;中国科学院计算技术研究所移动计算与新型终端北京市重点实验室;
【基金】：国家自然科学基金项目(61300131,61532002,61272322) 装备预研基金(9140A15030115DZ08042) 国家“八六三”高技术研究发展计划(2015AA016405)
【分类号】：J218.7;TP391.41
，
本文编号：2332786
[Abstract]:In view of the relationship between human body movement and garment deformation in clothing animation, the characteristics of human body motion and clothing deformation in clothing animation are defined and extracted firstly. Secondly, the high precision clothing animation case data of multiple sets of clothing under various human motion are established, and the relationship between them is learned from the examples based on four machine learning models. The experimental results of different learning models show that because there is a strong correlation between human body motion and garment deformation in clothing animation, the deformation distribution of clothing can be predicted more accurately by using human body motion. Compared with BP neural network, generalized regression neural network and support vector machine, the stochastic forest model can obtain the relationship between human body motion and garment deformation more effectively, and the final error can be controlled within an ideal range.
【作者单位】： 华北电力大学控制与计算机工程学院;中国科学院计算技术研究所移动计算与新型终端北京市重点实验室;
【基金】：国家自然科学基金项目(61300131,61532002,61272322) 装备预研基金(9140A15030115DZ08042) 国家“八六三”高技术研究发展计划(2015AA016405)
【分类号】：J218.7;TP391.41
，
本文编号：2332786
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