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Action unit recognition based on motion templates and GentleBoost

机译:基于运动模板和GentleBoost的动作单元识别

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To identify people's facial expressions, we need to accurately identify the Action Unit's motion. Generally, we locate facial feature points in images and then track them to identify Action Unites' motion. However, some Action Unites have not a clear outline and they can not be located and tracked actually. So we proposed an approach which can quickly and automatically identify Action Unites using Motion History Image feature based boosted classifiers. The detected face region is then divided into several relevant regions of interest, each of which contains an Action Unit. Through scanning the Motion History Image of the regions, we can get some motion segmentations. We classify these motion segmentations to identify whether there is an Action Unit. We tested our method with several videos, and the method has achieved an identifying rate of 97%.
机译:为了识别人们的面部表情,我们需要准确识别动作单元的动作。通常,我们在图像中找到面部特征点,然后对其进行跟踪以识别Action Unites的运动。但是,某些行动单位的轮廓并不清晰,因此无法进行实际定位和追踪。因此,我们提出了一种方法,该方法可以使用基于运动历史图像功能的增强分类器快速自动识别动作单位。然后将检测到的脸部区域划分为几个相关的感兴趣区域,每个区域都包含一个动作单元。通过扫描区域的运动历史图像,我们可以获得一些运动分割。我们对这些运动细分进行分类,以识别是否存在一个行动单位。我们用几个视频测试了我们的方法,该方法的识别率达到了97%。

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