【作者】 葛春宝；

【导师】 高文； 尹宝才；

【作者基本信息】 北京工业大学 ， 计算机应用技术， 2005， 硕士

【摘要】 近年来,运动捕获技术已经非常好的应用在计算机角色动画中。通过运动捕获设备,记录下演员的真实运动,然后把该运动数据重新应用到各种虚拟角色中。但当虚拟角色的大小和比例和表演人不一致时,其动作可能会失去原始运动的特点,本文提出一种新的运动重定向技术可以用于解决人体上肢运动重新定向问题。本文首先介绍了虚拟人建模标准,定义了建立的虚拟人模型,说明了模型的分层体系结构,其关节的关节分布及其拓扑关系,讲述了运动捕获设备在计算机动画中的重要作用和现有的各种运动捕获技术,重点介绍了基于数据手套的手语运动数据的捕获方法。然后本文提出了一种重新定向手语运动数据的方法。它把通过数据手套设备捕获的手语数据重新定向到具有不同大小和比例的虚拟人模型上,从而生成与源动作相同且真实自然的动画。具体方法如下:首先进行手势特征的分析,从而能在重定向后保存原先的手语含义,然后利用一种新的映射敏感点的方法把源运动中重要的特征映射到目标运动中,最后采用改进的反向运动学方法实现了手语运动的重定向。本文提出的方法已经成功的应用在新版中国手语电子辞典中,实验表明,提出的方法使得中国手语合成系统的可懂度提高30%以上。更多还原

【Abstract】 Recently, motion capture has become one of the most promising technologies in character animation. Realistic motion data can be captured by recording the movement of a real actor with a motion capture system, and motion retargeting will adapt these motion data to new character. While the target character is different from the original one, the target character is likely to lose desire features of original motion. The problem can be solved through motion retargeting technology. This thesis introduces the standard of the virtual human model, and builds our virtual human model firstly. Then we show the hierarchical structure of the model and the distribution of the joints. We also analyze the importance of motion capture device and focus on how to capture sign language data through data glove. With the assistance of data glove we propose a new method for retargeting sign language data to different virtual human model with different sizes and proportions. Realistic and natural animations can be produced to express similar meanings to the original. The proposed method first defines many sensitive points on the human body and selects the key sensitive points through analyzing the importance of the sensitive points. Next a novel mapping method based on relative position is presented to adapt the original sensitive points to the target sensitive points. Finally we utilize an IK solver to realize the retargeting problem. Our method had been applied in the new version of china sign language electronic dictionary. Experimental results show that the proposed method dramatically improves the recognition rate about 30%.更多还原