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The components of conversational facial expressions

机译:对话式面部表情的组成部分

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摘要

Conversing with others is one of the most central of human behaviours. In any conversation, humans use facial motion to help modify what is said, to control the flow of a dialog, or to convey complex intentions without saying a word. Here, we employ a custom, image-based, stereo motion-tracking algorithm to track and selectively "freeze" portions of an actor or actress's face in video recordings in order to determine the necessary and sufficient facial motions for nine conversational expressions. The results show that most expressions rely primarily on a single facial area to convey meaning, with different expressions using different facial areas. The results also show that the combination of rigid head, eye, eyebrow, and mouth motion is sufficient to produce versions of these expressions that are as easy to recognize as the original recordings. Finally, the results show that the manipulation technique introduced few perceptible artifacts into the altered video sequences. The use of advanced computer graphics techniques provided a means to systematically examine real facial expressions. This provides not only fundamental insights into human perception and cognition, but also yields the basis for a systematic description of what needs to be animated in order to produce realistic, recognizable facial expressions.
机译:与他人交谈是人类行为的最中心行为之一。在任何对话中,人类都使用面部动作来帮助修改所说的内容,控制对话的流程或传达复杂的意图而无需说一句话。在这里,我们采用了基于图像的自定义立体运动跟踪算法,以跟踪和选择性“冻结”视频录制中演员的脸部部分,以便为九种对话表达确定必要和足够的面部动作。结果表明,大多数表情主要依靠单个面部区域来传达含义,而不同表情使用不同的面部区域。结果还显示,刚硬的头部,眼睛,眉毛和嘴巴动作的组合足以产生这些表达式的版本,这些版本与原始录音一样容易识别。最后,结果表明,操纵技术几乎没有将可察觉的伪像引入改变后的视频序列中。先进计算机图形技术的使用提供了一种系统地检查真实面部表情的方法。这不仅提供了对人类感知和认知的基本见解,而且还为系统地描述了为制作逼真的,可识别的面部表情而需要进行动画处理的内容奠定了基础。

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