基于小波变换的运动分析及其应用

对捕获的运动数据进行编辑处理 ,是生成新的复杂人体动画和提高运动捕获数据重用性的关键 ,但目前大多数运动编辑技术不具备对运动进行高层控制处理的能力 ,为此 ,提出了一种基于小波变换的运动编辑新算法 ,即将小波变换引入运动编辑 ,并对运动信号进行多分辨率分析 ,从而实现了运动特征增强、运动融合及运动特征提取与综合 .实验结果表明 ,该算法非常适合对运动特征进行处理 ,由于其能够在高层次上对运动进行有效的编辑 ,因而提高了动画师的工作效率 .

Motion Analysis and Application Based on Wavelet Transformation

Motion editing is the key technology to improve the re-use of motion captured data and produce complex human animation. However, few techniques are capable of editing motion at high level. In this paper, wavelet transformation is introduced into motion multi-resolution analysis and some new algorithms, namely motion feature enhancement, motion fusion and motion feature extraction and synthesis, are proposed. Motion signal is decomposed into multi-resolution levels with wavelet analysis. The coarse level represents the overall pattern of a motion signal while the fine levels describe the details. Special motion style can be highlighted through enhancing the corresponding level content. And multiple motions can be fused by multi-resolution blending to create new motions somehow like to the blended motions. Special motion style can be synthesized into other motions by texturing them with related fine levels extracted from the related motions. The experiment shows that these algorithms are well suited for motion feature editing and enable animators to edit motion effectively at high level.