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Motion Dynamic Analysis of the Basic Facial Expressions

机译:基本面部表情的运动动力学分析

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In interaction systems, communication between user and the computer may be performed using a graphical display of human representation called avatar. This paper is focussed on the problem of facial motion analysis for human-like animation. Using similarities in motion data four criteria for characteristic points grouping (facial regions, movement directions, angles and distances) have been proposed. In order to estimate the number of clusters for selected facial expressions a dedicated algorithm has been applied. Based on the results of subjective assessment the most satisfying configuration of criteria, in terms of number of clusters and accuracy of emotions recognition, was a group of distance, region and angle between facial markers. In the result, the obtained groups may be used to simplify the number of control parameters necessary to syn-thesise facial expressions in virtual human systems. The final structure of the characteristic points can diminish overall computational resources usage by decreasing the number of points that need to be recalculated between animation phases. This is due to the fact, that the movement similarities were exploited to make the groups with the same properties be controlled by dominant markers.
机译:在交互系统中,可以使用称为化身的人类表示的图形显示来执行用户与计算机之间的通信。本文重点研究类人动画的面部运动分析问题。利用运动数据中的相似性,提出了四个特征点分组标准(面部区域,运动方向,角度和距离)。为了估计用于所选面部表情的聚类的数量,已经应用了专用算法。根据主观评估的结果,就簇的数量和情感识别的准确性而言,最令人满意的标准配置是一组面部标记之间的距离,区域和角度。结果,获得的组可用于简化在虚拟人系统中合成面部表情所需的控制参数的数量。特征点的最终结构可以通过减少动画阶段之间需要重新计算的点数来减少总体计算资源的使用。这是由于以下事实:利用运动相似性使具有相同属性的组受到显性标记的控制。

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