Image recognition of dance moving based on heterogeneous multiprocessor and dynamic image sampling

Motion capture technology has made great strides in computer science and information technology. The design of dance movements requires simulation and dancing of design elements to be critical to overcome the obstacle; 3d aesthetics need to be optimized and cause body rotation problems. Using image analysis technology to establish a mathematical model based on dance motion capture technology, it takes the five main dance movement components as the primary research object. It then proposes the continuity similarity of dance movement. Incorporate composite data obtained from samples during alignment. The proposed system's high tracking accuracy system indicates that it is suitable for various dance training programs based on the game. Video application product video studio software, and programming program, multimedia design of dance movement in the computer, and then realize the effect of dance technology in conjunction with computer technology. Finally, it provides a symbolic reference to dance movement technology research and design.     

动作捕捉技术在舞蹈姿态分析和教学中的实践研究

为了将人体运动仿真技术应用到舞蹈姿态分析和教学研究中。研究了舞蹈姿态动作捕捉及分析,包括舞蹈动作的实时采集,舞蹈姿态的模型数据库建立,以及基于特征平面向量的21个关键节点和7个特征匹配平面的舞蹈姿态分析方法;然后,以某健美操班50名学员为实例,划分舞蹈基础和身体素质相当的两组分别进行常规教学和试验教学,试验对比组除了在动作幅度上低于常规组3.9分外,其在动作力度、规范程度方面的打分相比均高出9分以上。研究将动作捕捉技术与舞蹈教学和分析相结合,实现了舞蹈动作的直观反馈和分析,为科学的舞蹈教学提供了数据支撑。     

Biomechanical evaluation of bike power saver

Bike power saver (BPS) is a new product that claims to change the angle of pedaling forces and reduce applied power dead range (Chic Sheng Industrial Co., Ltd, Taiwan, China). In order to determine its effectiveness, we quantified how BPS operates through a 3D kinematical study and electromyography (EMG) analysis of leg muscles during pedaling. Ten kinesiology students participated in this study. A 3D motion capture system consisting of nine high-speed cameras (VICON v8i, a capture rate of 120 frames/s) was used to collect the total body and pedal motion with and without BPS at statically determined low, middle and high intensity cycling levels. The short-time test (14s) was applied to all intensity levels while the long-time test (30 min) was applied only to the low wattage level. Wireless EMG was synchronized with the 3D motion capture system to monitor the right and left tibialis anterior, gastrocnemius, quadriceps and hamstring. The results revealed that BPS did not alter hip and knee movement significantly (p>0.05), but it did vary ankle movement. BPS caused a movement change in the pedals, and consequently induced instability in ankle control. The altered pedal movement led to an increase in activity level and presumably also energy expenditure for dominant muscles, resulting in a faster fatigue process. From these data, it is likely that the BPS actually requires more effort than a standard bike.     

基于特征向量匹配的舞蹈实时姿态分析方法

针对人体运动姿态可自由编辑的特性,提取人体骨架模型,建立人体运动姿态模型库,分析了运动捕捉系统在舞蹈训练中的应用,提出基于特征平面间相似性匹配的方法来计算模型各部件间运动数据参数。经过验证,该方法对于人体姿态的分析具有较高的准确性、鲁棒性,使得舞蹈演员能够准确的对比出与标准舞蹈动作的差异,为舞蹈者进行科学舞蹈训练提供了理论支持。     

Easy-to-use authoring system for Noh (Japanese traditional) dance animation and its evaluation

Noh is a genre of Japanese traditional theater, a kind of musical drama. Similar to other dance forms, Noh dance (shimai) can also be divided into small, discrete units of motion (shosa). Therefore, if we have a set of motion clips of motion units (shosa), we can synthesize Noh dance animation by composing them in a sequence based on the Noh dance notation (katatsuke). However, it is difficult for researchers and learners of Noh dance to utilize existing animation systems to create such animations. The purpose of this research is to develop an easy-to-use authoring system for Noh dance animation. In this paper, we introduce the design, implementation, and evaluation of our system. To solve the problems of existing animation systems, we employ our smart motion synthesis technique to compose motion units automatically. We improved the motion synthesis method by enhancing the algorithms for detecting body orientation and constraints between the foot and ground to handle Noh dance motions correctly. We classify motion units as either pattern units, which are specific forms of motion, represented as shot motion clips, or locomotion units, generated on the fly to denote movement towards a specific position or direction. To handle locomotion-type motion units, we implemented a module to generate walking motion based on a given path. We created several Noh dance animations using this system, which was evaluated through a series of experiments. We also conducted a user test to determine the usefulness of our system for learners of Noh dance.     

仿人足底肌电特征的机器人行走规划

模仿人类行走规律是规划双足机器人运动的基础.以往模仿人类步态主要通过视觉方法或惯性模块测量(Inertia measurement unit, IMU)方法捕捉人体特征点轨迹.这些方法不考虑零力矩点(Zero moment point, ZMP)的相似性.为解决该问题,本文提出了一种基于足底肌电信号(Electromyography, EMG)和惯性模块测量信号的混合运动规划方法.该方法通过测量足底肌电信号计算出足底压力中心的位置以及踝关节扭矩,结合惯性模块所测量的人体躯干和双足轨迹,来规划双足机器人的步态.首先,用肌电仪测量足底肌电信号,用惯性测量模块测量人体各肢体部分的姿态轨迹,经数据标定后作为仿人机器人的运动参考; 然后,通过预观控制输出稳定的步态.为确保仿人行走的效果,基于人体相似性对运动数据进行了步态优化.实验验证和分析表明, EMG信号超前ZMP约160ms,利用这个特性实现了对压力点位置的有效预测,提高了机器人在线模仿人类行走的稳定性.     

Silk road dance exhibition system based on motion capture

Silk Road dance is an excellent traditional Chinese dance drama, which has high artistic values. This article introduces the virtual performance techniques of Silk Road based on motion capture. First, obtain the dance data using motion capture technique according to the features of dance itself, then establish figure model, finally combines these data to make 3-D animation system to perform Silk Road, meanwhile designs some interfaces to introduce it. This system excavates details of the dance, and can be reference of man-machine interaction and animation production.     

基于动捕数据驱动的三维民族舞蹈展示方法

三维模型动画在数字化设计和应用中具有重要意义,受到越来越多研究者关注;但如何通过三维数字化原真再现民族舞蹈表演是极具挑战的问题.本论文通过动捕技术采集舞蹈动作实现舞蹈数字化展示.具体方法是:首先利用动捕设备捕获人体动作数据,然后在Maya中进行人物建模、骨骼绑定、蒙皮和权重调节,再通过MotionBuilder将3D模型与动捕数据结合,最终完成了现实舞蹈动作的虚拟人展演.论文构建了一个面向民族舞蹈展演的虚拟场景,并以13个民族的舞蹈为数字化内容,推广动捕驱动的舞蹈展演方法的应用.     

Analyzing motoric and physiological data in describing upper extremity movement in the aged

Cognitive functions, motoric expression, and changes in physiology are often studied separately, with little attention to the relationships or correlations among them. The study presented in this paper implements an integrated approach by combining motion capture (action) and EMG (physiological) parameters as synchronized data streams resulting from the action and associated physiological data. The reported experiments were designed to measure the preparatory movement capabilities of the upper extremities. In particular, measurement of changes in preparatory activity during the aging process is of interest in this context, as the attempt is to develop means to compensate for loss of adaptive capabilities that aging entails. To achieve this goal, it is necessary to quantify preparation phases (timing and intensity). Motion capture and EMG parameters were measured when subjects raised their arms without constraint (condition one) and raised their arms while holding a ball (second condition). Furthermore, on comparing aging and young participants, it was confirmed that with aging the temporal relationships between actual movement and the preceding EMG signal change.     

利用多源运动信息的下肢假肢多模式多步态识别研究

运动状态识别对智能下肢假肢的控制非常关键,本文利用下肢表面肌电信号、腿部角度和足底压力信号在运动模式和步态分析中的优势和特点,对下肢假肢的多模式多步态识别进行研究.通过建立下肢运动信息系统,获取下肢多源运动信息.先提取下肢肌电信号的小波包能量作为特征,建立多个HMM对下肢假肢的运动模式进行识别;再根据大小腿和膝关节的角...     

下肢表面肌电信号的降维和映射分析

肌电信号的采集和分析是外骨骼式康复机器人关节预测控制的重要基础之一.肌电信号数据量大并且复杂,相关性较高,信号处理通用性和高效性低,分析和预测人体运动信息误差大.采用最大自主等长收缩标准化处理算法,大大提高了表面肌电信号的通用性和泛化能力,并基于主成分分析方法,对肌电信号降维处理,利用神经网络实现与下肢的映射分析.实验结果表明,通过对比分析不同的降维处理方式,主成分降维后处理的肌电信号平均相关性达0.93,利用神经网络预测人体正常行走的下肢三关节运动角度,具有良好的可重复性和较高的精度,可以实现人体下肢肌电信号和各关节的映射控制.     

Target detection algorithm for dance moving images based on sensor and motion capture data

The effectiveness of classification based on motion capture data to identify the human skeleton dance types. The goal is based on the body joint's information is to perform the characteristic posture obtained by the ultra-high Kinect sensor, identifying for each dance. The proposed Target Detection (TD) algorithm is used to dance moving object identification based on the improved Gaussian Mixture Model (GMM). The proposed Target Detection (TD) algorithm based on a Gaussian Mixture Model is a widely used method for modeling background from a Kinect sensor moving objects. The used data set contains six folk dance sequences and their variations. Gesture recognition scheme using a plurality of time constraints, spatial information, and spatial distribution characteristics to create a training data set appropriate application. The Gaussian Mixed Model distribution background model account, the algorithm, and their frame difference can be extracted in straight lines to obtain target dance areas with less background and background photo station under motor damage conditions. Through real-time Target Detection (TD) algorithm dance moving images based on the Gaussian Mixture Model (GMM), these two algorithms effectively detect dance moving image targets.     

网络化手势运动跟踪系统设计

设计了一种基于微机电惯性传感器的数据手套.根据惯性导航和刚体动力学原理,构建了基于微型传感器的体感网络,并通过多传感器数据的融合解算以获取运动姿态信息,实现对手指各关节运动数据的捕获.结合计算机图形技术构建三维虚拟手捕获系统进行性能对比评估,实验结果表明:所设计的系统具有良好的稳定性和适应性,能够对手运动信息进行实时有效地捕获.     

Development of a motion analysis system using acceleration sensors for tennis and its evaluations

The term biological motion is often used by researchers studying the patterns of movement generated by living forms and in sports. We studied a pattern recognition system of motion in sport using biological motion data. Biological motion data are acquired using a 3D motion capture system. However, 3D motion capture systems are very expensive. In this article, a biological motion capture system was built using acceleration sensors. Our proposed system uses the technique of Gaussian fitting and regression analysis. We tested our proposed system in pattern recognition of outdoor tennis and its evaluations.     

Emotion Analysis and Classification: Understanding the Performers' Emotions Using the LMA Entities

The increasing availability of large motion databases, in addition to advancements in motion synthesis, has made motion indexing and classification essential for better motion composition. However, in order to achieve good connectivity in motion graphs, it is important to understand human behaviour; human movement though is complex and difficult to completely describe. In this paper, we investigate the similarities between various emotional states with regards to the arousal and valence of the Russell's circumplex model. We use a variety of features that encode, in addition to the raw geometry, stylistic characteristics of motion based on Laban Movement Analysis (LMA). Motion capture data from acted dance performances were used for training and classification purposes. The experimental results show that the proposed features can partially extract the LMA components, providing a representative space for indexing and classification of dance movements with regards to the emotion. This work contributes to the understanding of human behaviour and actions, providing insights on how people express emotional states using their body, while the proposed features can be used as complement to the standard motion similarity, synthesis and classification methods.     

基于骨架信息的民族舞蹈典型动作识别

民族舞蹈是中国重要的非物质文化遗产,在动作识别技术应用十分广泛的环境下,对于民族舞蹈文化保护和传承的研究领域还比较空白。为了更好地保护和传承少数民族舞蹈,筛选了5类少数民族舞蹈典型动作片段,结合深度摄像机开发了动作数据采集系统,通过该系统采集民族舞蹈动作骨架信息,构建了民族舞蹈典型动作数据集,使用改进的三维卷积神经网络（3D CNNs）模型对民族舞蹈动作骨架序列进行了识别与分类,并且与其他经典动作识别方法进行了对比,该方法在实验中获得了95%的识别率。研究结果表明,该民族舞蹈数据集构建方法合理,识别模型对民族舞蹈分类有良好的性能,对民族舞蹈动作进行了有效的记录和保存,为民族舞蹈数字化保护提供一种新的方式。     

一种光学式运动捕捉系统下的物体运动数据捕捉方法研究

多相机视觉运动捕捉系统能通过捕捉标记点的空间坐标来获得运动物体的运动学参数,文中提出了一种基于多相机运动捕捉系统下的通用物体运动数据捕捉方法;首先根据3个标记点组成固定模型获取物体运动过程中对应标记点的瞬时坐标,然后通过向量法求解出被测物体在运动过程中各采集点对应的物体位姿,然后通过卡尔曼滤波方法消除运动捕捉过程中的系统和环境误差的影响,获得平滑的物体位姿运动轨迹,并根据滤波数据计算出物体在各采集点对应的速度、加速度、角速度、角加速度;最后基于协作机器人进行物体的运动数据捕捉实验,验证了所提出物体运动数据捕捉方法的正确性。     

Virtual Force/Tactile Sensors for Interactive Machines Using the User's Biological Signals

This study proposes a new approach to virtual realization of force/tactile sensors in machines equipped with no real sensors. The key of our approach is that a machine exploits the user's biological signals. Therefore, this approach is not dependent on controlled objects and is expected to be widely applicable for a variety of machines including robots. This article describes an example robotic system comprised of an industrial robot manipulator, a motion capture system and a surface electromyogram (EMG) measurement apparatus. By monitoring/recording the user's surface EMG and postural information in real-time, we show that a robot equipped with no force/tactile sensors behaved similarly to one possessing sensors over its body. Another advantage of our approach is demonstrated by a task in which a robot and a user cooperatively hold and move a heavy load.     

基于多自主智能体的群体动画创作

群体动画一直是计算机动画界一个具有挑战性的研究方向，提出了一个基于多自主智能体的群体动画创作框架：群体中的各角色作为自主智能体，能感知环境信息，产生意图，规划行为，最后通过运动系统产生运动来完成行为和实现意图，与传统的角色运动生成机理不同，首先采用运动捕获系统建立基本运动库，然后通过运动编辑技术对基本运动进行处理以最终得到角色运动，应用本技术，动画师只需“拍摄”角色群体的运动就能创作群体动画，极大地提高了制作效率。     

人体运动数据重构方法进展*

运动捕捉系统产生的人体运动数据是标记点在运动序列中的位置数据,用于驱动人体模型产生真实感的动画。在对近几年有关人体运动数据重构的文献进行综合和分析的基础上,首先对人体运动数据重构进行了问题描述,并对人体运动数据在重构过程中难以避免的噪声问题和特征点(虚拟空间中的标记点)缺失问题的研究分别进行了总结和分析;然后对人体运动数据获取的光学式原型捕捉系统开发的研究进行了讨论,评述了人体运动数据驱动人体几何模型的相关研究;最后对未来研究提出了一些展望。