数据局部特征驱动的人体运动合成方法研究
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摘要
人体运动合成技术是计算机动画技术的重要组成部分,可细分为模型驱动和数据驱动两大类方法,基于后者的人体运动合成技术在现阶段更适合于构建自然、真实的人体全身运动动画。目前,在数据驱动人体运动合成的主流方法中,存在着人工定制过多,对样本的依赖性较强等问题。本文从运动的局部特征入手,以人体运动合成中的运动过渡生成、无滑步位移运动生成以及虚拟人的实时控制等运动合成中的关键环节为研究对象,探索了解决前述问题的有效途径与方法。提出了基于拉普拉斯坐标的运动过渡生成算法、基于接触的运动图的虚拟人位移运动生成方法和支持实时交互控制的虚拟人运动合成方法。
运动过渡生成是数据驱动人体运动合成的基本技术。为了减少人工定制、减轻对样本的依赖,提出基于拉普拉斯坐标的运动过渡生成算法。将人体运动表示为多维向量空间中采用顶点集合定义的曲线段,利用顶点代表运动某一帧中若干个通道的数据,利用顶点间的邻域关系代表这些数据之间的时序关系,进而利用关于顶点的拉普拉斯坐标来表示运动在时间上的局部特征。在尽量保持拉普拉斯坐标不变的情况下将代表两段运动的曲线段进行拼接,生成这两段运动之间的运动过渡。实验结果表明,该方法只需要分别指定两段运动中参与过渡的帧数就可以生成平滑的、同时带有两段输入运动局部特征的运动过渡。由于无需为每个参与过渡的帧分配权值,同时无需通过对样本的学习来生成运动过渡,该方法的人工定制因素更少且样本依赖程度更低。
滑步现象是数据驱动人体运动合成中常见的失真现象。为了避免对大量样本的搜索和优化,直接生成无滑步的运动,提出基于接触的运动图并将其应用于虚拟人位移运动的生成。利用运动中人体足部与地面接触的局部信息构建基于接触的运动图。结合图上节点和边在改变运动方向上的不同可能性,利用它们蕴含的足部与地面的局部接触信息,通过对图上运动序列进行调整,直接生成沿水平地面上指定路径行进的无滑步位移运动。实验结果表明,利用基于接触的运动图,只需很少的样本就能够直接生成无滑步的虚拟人位移运动,且能够包含双足腾空的运动片段。由于无需通过对大量相关样本进行优化和搜索来去除滑步现象,这种方法对样本的要求大大降低。
根据用户输入实时生成无滑步的全身运动在现阶段主流应用系统中难以实现。为了使虚拟人能够实时响应用户输入生成无滑步位移运动,提出支持实时交互控制的虚拟人运动合成方法。利用面向基于接触的运动图路径匹配算法中匹配单元的局部性,将不同时刻的待匹配路径看做不同输入,在每个时间片中对当前待匹配路径执行最多一步匹配,实现支持动态路径的在线匹配。通过动态改变待匹配路径,实现对虚拟人位移运动的实时控制。实验结果表明,该方法能够根据用户的输入实时地自动生成符合要求的虚拟人无滑步位移运动。由于在运行过程中无需针对各种特殊情况分别考虑虚拟人的响应策略,该方法所需要的人工定制更少。
研究显示,利用运动数据的局部特征,能够有效减少人体运动合成中的人工定制,减轻对样本的依赖,提高数据驱动运动合成的自动化程度。
Human motion synthesis is an important part in the area of computer graphics, which can be divided to model-based and data-driven ones. Compared to model-based ones, data-driven methods of human motion synthesis are more suitable for producing nature-looking whole-body human motions currently. Though, there are defects in mainstream data-driven technologies including too much manual customizations and high sample dependence. Considering local features of motions, some key issues in data-driven motion synthesis were explored and researched including motion transition generation, foot-skate free locomotion production and real-time control for virtual characters. In this thesis, we proposed Laplacian coordinates based motion transition generation, contact-based motion graphs and real-time foot-skate free locomotion synthesis supporting interative control.
Motion transition generation is a basic technology in data-driven human motion synthesis. Laplacian coordinates based motion transition generation was proposed to reduce the manual customization and sample dependence. At first, motions were mapped to a curve segment in a multidimentional vector space, while each vetex represented mult-channel data in a frame and the neighborhood of each vertex represented the temporal relationship of the frames. Then the Laplacian coordinates of each vertex can represent the temporal local features near the time it formed. By connecting two curve segments representing two motions, a motion transition between these two motions can be formed from the result curve segment. Experimental results show that when the numbers of frames used to produce transitions in two input motions are decided, our method can generate smooth motion transitions with local features of both input motions. Without the need of arranging weights for each frames and the process of learning to find rules for generating new motions, this method possessed less manual customization and lower sample dependence.
Foot-skate is a common kind of error when motions are synthesized from samples. To produce foot-skate free locomotions directly avoiding searching and optimizing on lots of samples, contact-based motion graphs were proposed and applied to generate locomotions for virtual actors. At first, information of the feet contacting with ground was used to build contact-based motion graphs. The nodes and edges in this graph differed in the possibility of changing motion direction while keeping poses and feet unchanged. According to contact information in these elements, new foot-skate free motions along user-defined paths on ground can then be generated directly by adjusting motion sequences exacted from the graph. Experimental results show that with the help of contact-based motion graphs, our method can produce foot-skate free locomotions for virtual actors with little samples, even when flying motion clips are included. Thus, this method can reduce the sample dependence dramatically as foot-skate cleanup based on searching or optimizing on lots of samples are no longer needed.
Real-time controllable foot-skate free whole-body motions are difficult to synthesiz by mainstream applications currently. To make virtual actors can perform foot-skate locomotions according to user input in real-time, the method of motion synthesis supporting interactive control for virtual actors was proposed. At first, online path adaption was implemented based on the localty of adapting unit in path adaptation for contact-based graphs. Unadapted paths at different time were treated as different inputs. When an input was processed, at most one step of adaptation would be performed. By changing paths unadapted dynamically, users can control locomotions of virtual actors in real-time.Experimental results show that our method can make foot-skate free interactively controllable locomotions for virtual actors automatically. The manual customization in our method was reduced because there was no need to define feed-back strategies for virtual actors in many cases.
As shown in our researches, with the help of local features of motions, the automation of data-driven motion synthesis can be improved for the reduction of manual customization and sample dependence.
运动过渡生成是数据驱动人体运动合成的基本技术。为了减少人工定制、减轻对样本的依赖,提出基于拉普拉斯坐标的运动过渡生成算法。将人体运动表示为多维向量空间中采用顶点集合定义的曲线段,利用顶点代表运动某一帧中若干个通道的数据,利用顶点间的邻域关系代表这些数据之间的时序关系,进而利用关于顶点的拉普拉斯坐标来表示运动在时间上的局部特征。在尽量保持拉普拉斯坐标不变的情况下将代表两段运动的曲线段进行拼接,生成这两段运动之间的运动过渡。实验结果表明,该方法只需要分别指定两段运动中参与过渡的帧数就可以生成平滑的、同时带有两段输入运动局部特征的运动过渡。由于无需为每个参与过渡的帧分配权值,同时无需通过对样本的学习来生成运动过渡,该方法的人工定制因素更少且样本依赖程度更低。
滑步现象是数据驱动人体运动合成中常见的失真现象。为了避免对大量样本的搜索和优化,直接生成无滑步的运动,提出基于接触的运动图并将其应用于虚拟人位移运动的生成。利用运动中人体足部与地面接触的局部信息构建基于接触的运动图。结合图上节点和边在改变运动方向上的不同可能性,利用它们蕴含的足部与地面的局部接触信息,通过对图上运动序列进行调整,直接生成沿水平地面上指定路径行进的无滑步位移运动。实验结果表明,利用基于接触的运动图,只需很少的样本就能够直接生成无滑步的虚拟人位移运动,且能够包含双足腾空的运动片段。由于无需通过对大量相关样本进行优化和搜索来去除滑步现象,这种方法对样本的要求大大降低。
根据用户输入实时生成无滑步的全身运动在现阶段主流应用系统中难以实现。为了使虚拟人能够实时响应用户输入生成无滑步位移运动,提出支持实时交互控制的虚拟人运动合成方法。利用面向基于接触的运动图路径匹配算法中匹配单元的局部性,将不同时刻的待匹配路径看做不同输入,在每个时间片中对当前待匹配路径执行最多一步匹配,实现支持动态路径的在线匹配。通过动态改变待匹配路径,实现对虚拟人位移运动的实时控制。实验结果表明,该方法能够根据用户的输入实时地自动生成符合要求的虚拟人无滑步位移运动。由于在运行过程中无需针对各种特殊情况分别考虑虚拟人的响应策略,该方法所需要的人工定制更少。
研究显示,利用运动数据的局部特征,能够有效减少人体运动合成中的人工定制,减轻对样本的依赖,提高数据驱动运动合成的自动化程度。
Human motion synthesis is an important part in the area of computer graphics, which can be divided to model-based and data-driven ones. Compared to model-based ones, data-driven methods of human motion synthesis are more suitable for producing nature-looking whole-body human motions currently. Though, there are defects in mainstream data-driven technologies including too much manual customizations and high sample dependence. Considering local features of motions, some key issues in data-driven motion synthesis were explored and researched including motion transition generation, foot-skate free locomotion production and real-time control for virtual characters. In this thesis, we proposed Laplacian coordinates based motion transition generation, contact-based motion graphs and real-time foot-skate free locomotion synthesis supporting interative control.
Motion transition generation is a basic technology in data-driven human motion synthesis. Laplacian coordinates based motion transition generation was proposed to reduce the manual customization and sample dependence. At first, motions were mapped to a curve segment in a multidimentional vector space, while each vetex represented mult-channel data in a frame and the neighborhood of each vertex represented the temporal relationship of the frames. Then the Laplacian coordinates of each vertex can represent the temporal local features near the time it formed. By connecting two curve segments representing two motions, a motion transition between these two motions can be formed from the result curve segment. Experimental results show that when the numbers of frames used to produce transitions in two input motions are decided, our method can generate smooth motion transitions with local features of both input motions. Without the need of arranging weights for each frames and the process of learning to find rules for generating new motions, this method possessed less manual customization and lower sample dependence.
Foot-skate is a common kind of error when motions are synthesized from samples. To produce foot-skate free locomotions directly avoiding searching and optimizing on lots of samples, contact-based motion graphs were proposed and applied to generate locomotions for virtual actors. At first, information of the feet contacting with ground was used to build contact-based motion graphs. The nodes and edges in this graph differed in the possibility of changing motion direction while keeping poses and feet unchanged. According to contact information in these elements, new foot-skate free motions along user-defined paths on ground can then be generated directly by adjusting motion sequences exacted from the graph. Experimental results show that with the help of contact-based motion graphs, our method can produce foot-skate free locomotions for virtual actors with little samples, even when flying motion clips are included. Thus, this method can reduce the sample dependence dramatically as foot-skate cleanup based on searching or optimizing on lots of samples are no longer needed.
Real-time controllable foot-skate free whole-body motions are difficult to synthesiz by mainstream applications currently. To make virtual actors can perform foot-skate locomotions according to user input in real-time, the method of motion synthesis supporting interactive control for virtual actors was proposed. At first, online path adaption was implemented based on the localty of adapting unit in path adaptation for contact-based graphs. Unadapted paths at different time were treated as different inputs. When an input was processed, at most one step of adaptation would be performed. By changing paths unadapted dynamically, users can control locomotions of virtual actors in real-time.Experimental results show that our method can make foot-skate free interactively controllable locomotions for virtual actors automatically. The manual customization in our method was reduced because there was no need to define feed-back strategies for virtual actors in many cases.
As shown in our researches, with the help of local features of motions, the automation of data-driven motion synthesis can be improved for the reduction of manual customization and sample dependence.
引文
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