面向肌电信号的虚拟现实提线木偶动画研究
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谭宇彤(1998-),女,江西九江人,学士,主要研究领域为自然语言处理,含文本风格迁移,文本生成;税午阳(1983-),男,博士,高级工程师, CCF专业会员,主要研究领域为文化遗产数字化保护,颅骨面貌复原;周旭峰(1996-),男,学士,主要研究领域为社会计算,含情感分析,大数据处理;付艳(1980-),女,博士,副教授,CCF专业会员,主要研究领域为大数据分析,机器学习;孔令芝(1998-),女,学士,主要研究领域为计算机网络与信息安全,信息隐藏;周明全(1954-),男,博士,教授,博士生导师,CCF杰出会员,主要研究领域为计算机可视化技术,软件工程,中文信息处理;王醒策(1977-),女,博士,教授,博士生导师,CCF专业会员,主要研究领域为虚拟现实,人工智能,机器学习,医学影像处理;Vladimir KORKHOV(1977-),男,博士,研究员,博士生导师,主要研究领域为高性能并行计算,虚拟机分配,数据可视化,大数据处理;武仲科(1965-),男,博士后,教授,博士生导师,CCF高级会员,主要研究领域为计算机图形学,计算机辅助几何设计,计算机动画,虚拟现实,医学图像处理;Luciano Paschoal GASPARY(1974-),男,博士,教授,博士生导师,主要研究领域为计算机网络,云计算,分布式系统.

通讯作者:

王醒策,E-mail:wangxingce@bnu.edu.cn;武仲科,E-mail:zwu@bnu.edu.cn

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基金项目:

国家重点研发计划政府间重点专项金砖国家合作项目(2017YFE0100500);国家科技支撑计划(2017YFB1002604,2017YFB1402100;2017YFB 1002804);北京市自然科学基金(4172033)


Research on Puppet Animation Controlled by Electromyography (EMG) in Virtual Reality Environment
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National Key Research and Development Plan of of Cooperation between the BRICS of China (2017YFE 0100500); National Key R&D Program of China (2017YFB1002604, 2017YFB1402105, 2017YFB1002804); Beijing Natural Science Foundation of China (4172033)

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    摘要:

    泉州提线木偶属于首批中国非物质文化遗产,是中华传统文化的实现形式之一.然而,由于木偶体积庞大,携带与操作不便,直接限制了其受众群体.为了实现提线木偶的有效传承与保护,设计了基于手势识别的虚拟现实提线木偶动画方案,构建了基于MYO臂环肌电信号的人体生理信号控制动画原型系统,应用两个用户实验验证了算法的高精确性与易操控性.首先,通过低通滤波与平滑实现多通道肌电信号数据的信号处理.其次,提取八通道时域特征与时频域特征,并通过线性判别器将其降维为六维特征向量,实现特征间关联性消除与算法鲁棒性增强.最后,构造多分类支撑向量机实现特征向量,确定手势识别结果.实验验证算法离线动作平均识别准确率为95.59%,实时动作平均识别准确率达到90.75%,在1.1s左右完成手势识别.面向提线木偶任务,构造了两个用户体验任务,普通用户人群中,木偶动作识别率较高,用户使用意愿、易学性等方面,系统性能亦显著高于真实木偶操控;专业用户在承认系统可用性的同时,具有较高的接受度.用户任务表明该设计满足了手势识别实时性和准确性的要求,具有良好的交互性和趣味性.相关研究可以广泛地应用于计算机动画等类似的系统,对于体验和保护提线木偶具有现实意义.

    Abstract:

    Quanzhou puppet is one of the intangible cultural heritages of China. It is the physical embodiment of traditional Chinese culture. However, the large size of the puppet and inconvenience to carry and manipulate directly makes it hard to reach a wider audience. In order to realize the effective inheritance and protection of Quanzhou puppet, this study designs a virtual real-line puppet animation scheme based on gesture recognition, builds a prototype system which uses MYO Armband EMG signal to control the generation of animation, and applies it in user experiment to verify the high accuracy and easy manipulation of the algorithm. Firstly, low-pass filtering and smoothing is used to process the original multi-channel EMG data. Secondly, after eight-channel EMG signal time-domain feature and time-frequency-domain feature extraction, the dimension of the feature vector is reduced to six by linear discriminator to eliminate the correlation between features and enhance the robustness of the algorithm. Thirdly, a multi-class support vector machine is constructed which uses feature vector to determine the result of gesture recognition. Experiments show that the average recognition accuracy of offline action is 95.59%, the average recognition accuracy of real-time action is 90.75%, and the gesture recognition is completed within 1.1 s. For the puppet task, two users task is designed:the common users and the expert users. In the common user study, the gestures recognition accuracy is high. In the aspects of user's willingness to use and easiness to learn, the performance of this system is significantly higher than real puppets manipulation. In the expert user study, user's acceptance and usability of the system are also highly evaluated. These two user tasks indicate the system meets the requirements of real-time and accuracy, and has good interactivity and interesting. Relevant research can be widely applied to similar systems, such as computer animation. It has practical significance for experiencing and protecting the puppet.

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谭宇彤,周旭峰,孔令芝,王醒策,武仲科,税午阳,付艳,周明全,Vladimir KORKHOV, Luciano Paschoal GASPARY.面向肌电信号的虚拟现实提线木偶动画研究.软件学报,2019,30(10):2964-2985

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  • 收稿日期:2018-08-19
  • 最后修改日期:2018-11-01
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  • 在线发布日期: 2019-05-16
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