基于低维特征的虚拟人运动及位姿生成
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摘要
运动捕获设备的广泛使用,产生了大量的人体运动数据,为人体运动生成提供便利的同时,也带来了分类、标记、检索等多方面的问题。此外,人体拓扑结构复杂且关节数量多,直接利用高维变量来生成人体运动非常困难。针对这些问题,本文以运动数据的组织、降维和查找为主线,在构造对应低维特征空间的基础上,对真实感触碰运动及基于草绘的人体位姿生成方法进行了深入研究。
针对现有触碰运动合成算法在灵活性和真实感等方面的不足,本文提出了一种基于生物力学的真实感触碰控制器(BLRC)。BLRC从生物力学研究领域引入了多个不同的触碰策略,并利用手臂触碰工作区来指导数据采样。为不同的触碰策略构造对应的低维空间,使得BLRC可以在低维空间中快速进行最优化求解。
为了进一步提高触碰运动的真实感,本文提出了基于组合控制器的触碰运动生成框架。利用低维人体运动特征,我们构造了四个生成具体触碰运动的静态控制器和三个连接静态控制器的过渡控制器。实验表明,包含这些控制器的算法框架能够有效展现出人类触碰行为中的试探性过程。
为了帮助用户快速创建正确的虚拟人位姿,本文提出了一个用户友好的三维人体位姿草绘系统。通过对高维图像描述符进行低维空间映射,系统实现了对大规模三维人体位姿的快速查找。在用户绘制的过程中,系统通过在绘图板上给用户提供相应的反馈信息来帮助他们进行下一笔的绘制。
The wide application of motion capture equipment brings more and more motion data, although these data can provide sufficient support for human motion generation, the large amount of data also brings a series of difficult problems in classification, marking, retrieval, storage and so on. In addition, the topological structure of the human body is so complex and too many controllable variables are involved, that it becomes a very difficult problem for directly controlling human movement through manipulating these high dimensional variables. To solve these problems, we focus on the organization, dimensionality reduction and search for motion data. Based on corresponding low-dimensional feature space, we study on the approaches for character motion and posture concerning to reaching and sketching-based system.
To overcome the defects of flexibility and realism for existing algorithms for reaching motion synthesis, we present a Biomechanics-based Life-like Reaching Controller (BLRC). BLRC employs various reaching strategies borrowed from biomechanics and exploits the arm-reachable workspace to guide the motion sampling. Through constructing different low-dimensional spaces for reaching strategies, the BLRC can solve the optimization problem in the low-dimensional space quickly.
To further improve the realism of reaching motion, we present a controller-based framework for reaching motion synthesis. Based on low-dimensional motion feature, we construct four stationary controllers to generate concrete reaching motion and three transition controllers to stitch these stationary controllers. The experiments show that our framework can express the inherent tentative process for human reaching effectively.
In order to facilitate users to create a right human posture quickly, we create a user-friendly sketch-based character posing system. By mapping the high-dimensional image descritptor into low-dimensional space, our system realizes the fast retrieval of3D character pose in a large database. While the user is sketching, our system is able to provide some feedback information to help him/her to draw next stroke.
针对现有触碰运动合成算法在灵活性和真实感等方面的不足,本文提出了一种基于生物力学的真实感触碰控制器(BLRC)。BLRC从生物力学研究领域引入了多个不同的触碰策略,并利用手臂触碰工作区来指导数据采样。为不同的触碰策略构造对应的低维空间,使得BLRC可以在低维空间中快速进行最优化求解。
为了进一步提高触碰运动的真实感,本文提出了基于组合控制器的触碰运动生成框架。利用低维人体运动特征,我们构造了四个生成具体触碰运动的静态控制器和三个连接静态控制器的过渡控制器。实验表明,包含这些控制器的算法框架能够有效展现出人类触碰行为中的试探性过程。
为了帮助用户快速创建正确的虚拟人位姿,本文提出了一个用户友好的三维人体位姿草绘系统。通过对高维图像描述符进行低维空间映射,系统实现了对大规模三维人体位姿的快速查找。在用户绘制的过程中,系统通过在绘图板上给用户提供相应的反馈信息来帮助他们进行下一笔的绘制。
The wide application of motion capture equipment brings more and more motion data, although these data can provide sufficient support for human motion generation, the large amount of data also brings a series of difficult problems in classification, marking, retrieval, storage and so on. In addition, the topological structure of the human body is so complex and too many controllable variables are involved, that it becomes a very difficult problem for directly controlling human movement through manipulating these high dimensional variables. To solve these problems, we focus on the organization, dimensionality reduction and search for motion data. Based on corresponding low-dimensional feature space, we study on the approaches for character motion and posture concerning to reaching and sketching-based system.
To overcome the defects of flexibility and realism for existing algorithms for reaching motion synthesis, we present a Biomechanics-based Life-like Reaching Controller (BLRC). BLRC employs various reaching strategies borrowed from biomechanics and exploits the arm-reachable workspace to guide the motion sampling. Through constructing different low-dimensional spaces for reaching strategies, the BLRC can solve the optimization problem in the low-dimensional space quickly.
To further improve the realism of reaching motion, we present a controller-based framework for reaching motion synthesis. Based on low-dimensional motion feature, we construct four stationary controllers to generate concrete reaching motion and three transition controllers to stitch these stationary controllers. The experiments show that our framework can express the inherent tentative process for human reaching effectively.
In order to facilitate users to create a right human posture quickly, we create a user-friendly sketch-based character posing system. By mapping the high-dimensional image descritptor into low-dimensional space, our system realizes the fast retrieval of3D character pose in a large database. While the user is sketching, our system is able to provide some feedback information to help him/her to draw next stroke.
引文
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