Optimization‐based group performance deducing

Large‐scale group performance animation has been an important research topic because of its diverse range of applications including virtual rehearsal and film production. Animating hundreds of virtual actors as what the director wishes is a tough task. In this paper, we address this challenge by introducing an optimization method that generates large‐scale group performance by deducing a small‐scale one with fewer actors. We introduced group motion bigraph technique and transformed the motion‐deducing problem into a constrained optimization problem. A solving process is then presented to automatically obtain the motion of the large group with velocity constraints. Moreover, an interactive system of constructing the group motion bigraph has been implemented, which provides flexible edit and control on deducing group motion. The animation results show that our method is competent for deducing large‐scale group performance from only several motion clips performed by small groups. Copyright © 2013 John Wiley & Sons, Ltd.     

人体运动的函数数据分析与合成

在许多虚拟现实的应用中,虚拟人作为人在计算机中的表示,是提高其交互能力和沉浸感的重要因素之一.然而,对于虚拟人建模而言,合成逼真、可控的虚拟人运动仍然是具有挑战性的课题.为此,提出了一种基于函数数据分析的人体运动合成方法.通过对一组样本运动进行函数主成分分析,构建出一个由特征运动构成的低维函数子空间.该低维子空间不仅能够有效地刻画样本序列内在的变化规律,而且也为有目的的运动合成提供了方法.在该空间中,通过控制各特征运动的系数即可合成出逼真、平滑的运动序列.该合成过程没有耗时的计算,因此能够满足各种实时应用     

基于VRML的中国手语三维显示

手语合成的目的是由计算机自动生成文本句子对应的手语，是智能人机接口研究的一个极具挑战性的课题。手语显示是手语合成过程中非常关键的一步，其任务是在文本句子转换为手语码后，将手语码逼真地显示成虚拟人手语运动。介绍了研究中国手语合成时提出的一种基于VRML的三维虚拟人姿态显示方法和连续中国聋人手语显示方法。该方法不仅可以显示逼真的虚拟人合成手语，而且具有很好的通用性，为网络环境中实现不同人体模型的手语表达与传输打下了基础。     

Planning interactive task for intelligent characters

Motion planning is an important problem in character animation and interactive simulation. However, few planning methods have considered domain‐specific knowledge that governs the agent's behaviors, and none of them is capable of planning the interactive task in which the agent interacts with the objects in the virtual environment. This paper presents a novel method to plan the interactive task based on Q‐learning for intelligent characters. The approach can be described as a three‐phase framework: data preprocessing phase, controller learning phase, and motion‐synthesis phase. In the data preprocessing phase, we abstract the motion clips as high‐level behaviors and construct the interactive behavior graph (IBG) to define the interactive capabilities of the agent in terms of interactive features. For the controller training phase, with IBG, Q‐learning algorithm is employed to train the control policy in the discrete domain with interactive features. In the motion‐synthesis phase, the optimal motion sequences can be generated by following the policy to accomplish the interactive task finally. The experimental results demonstrate that the uniform framework can generate reasonable and realistic motion sequences to plan interactive task in complex environment. Copyright © 2012 John Wiley & Sons, Ltd.     

基于非线性流形学习的3维人体运动合成

为了实现3维人体运动的有效合成,提出了一种基于非线性流形学习的3维人体运动合成框架及算法,并可应用于方便、快捷、用户可控的3维人体运动合成。该合成算法框架先采用非线性流形降维方法将高维运动样本映射到低维流形上,同时求解其本征运动语义参数空间的表达,然后将用户在低维运动语义参数空间中交互生成的样本通过逆向映射重建得到具有新运动语义特征的3维运动序列。实验结果表明该方法不仅能够对运动物理参数（如特定关节的运动位置、物理运动特征）进行较为精确的控制,还可用于合成具有高层运动语义（运动风格）的新运动数据。与现有运动合成方法比较,该方法具有用户可控、交互性强等优点,能够应用于常见3维人体运动数据的高效生成。     

Real Time Animation of Virtual Humans: A Trade‐off Between Naturalness and Control

Virtual humans are employed in many interactive applications using 3D virtual environments, including (serious) games. The motion of such virtual humans should look realistic (or ‘natural’) and allow interaction with the surroundings and other (virtual) humans. Current animation techniques differ in the trade‐off they offer between motion naturalness and the control that can be exerted over the motion. We show mechanisms to parametrize, combine (on different body parts) and concatenate motions generated by different animation techniques. We discuss several aspects of motion naturalness and show how it can be evaluated. We conclude by showing the promise of combinations of different animation paradigms to enhance both naturalness and control.     

Presence and interaction in mixed reality environments

In this paper, we present a simple and robust mixed reality (MR) framework that allows for real-time interaction with virtual humans in mixed reality environments under consistent illumination. We will look at three crucial parts of this system: interaction, animation and global illumination of virtual humans for an integrated and enhanced presence. The interaction system comprises of a dialogue module, which is interfaced with a speech recognition and synthesis system. Next to speech output, the dialogue system generates face and body motions, which are in turn managed by the virtual human animation layer. Our fast animation engine can handle various types of motions, such as normal key-frame animations, or motions that are generated on-the-fly by adapting previously recorded clips. Real-time idle motions are an example of the latter category. All these different motions are generated and blended on-line, resulting in a flexible and realistic animation. Our robust rendering method operates in accordance with the previous animation layer, based on an extended for virtual humans precomputed radiance transfer (PRT) illumination model, resulting in a realistic rendition of such interactive virtual characters in mixed reality environments. Finally, we present a scenario that illustrates the interplay and application of our methods, glued under a unique framework for presence and interaction in MR.     

一种基于传感器的人体上肢运动实时跟踪方法

实时跟踪人体运动是人机交互的重要研究课题,可以广泛应用于虚拟现实、虚拟人运动合成、聋人手语自动生成、计算机3D动画、机器人运动控制、远程人机交互等领域。文中介绍了一种基于传感器的人体上肢运动实时跟踪方法,给出了该方法的虚拟人模型、计算原理与校正方法,最后介绍了整个方法的实现以及在中国聋人手语自动合成中的应用。该方法具有使用传感器少,运动跟踪精度高、计算过程简单而且速度快等特点。     

基于运动捕获数据的虚拟人动画研究

随着三维游戏等行业对计算机动画制作需求的增加,在三维动画制作软件中人工调整虚拟人动作的工作方式已经不再适合现在的计算机动画制作。运动捕获技术是直接记录物体的运动数据并将其用于生成计算机动画,具有高效率、所生成的动画真实感强等优点,因而获得了广泛应用。提出了一种利用运动捕获数据来生成动画的方法,基于运动捕获得到的数据建立并驱动三维骨架模型,从而产生骨架的运动,形成动画。该方法可以充分利用现有的大量运动捕获数据,因此具有较大的应用前景。     

基于参数化运动合成的运动图构建及其应用

虚拟人运动的可控性和逼真性是虚拟现实应用中追求的重要目标,为了实现对虚拟人的灵活控制,合成出逼真的运动序列,提出了基于参数化运动合成的运动图方法.运动图的结点中存储了具有明确含义的控制参数,通过改变控制参数合成不同的运动片段,可以实现对虚拟人的灵活控制;提出了一种改进的运动融合方法,运动图的边将不同运动片段进行融合,有效的避免了脚步滑动和根关节朝向抖动的产生.根据用户对交互控制和路径轨迹的不同应用需求设计实验,实验结果表明,方法不仅具有较高的控制精度,而且合成的运动序列逼真自然.