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Effective distance measure for unusual facial expression detection of human face images

机译:人脸图像异常面部表情检测的有效距离措施

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In this paper, a simple method for the facial expression detection to identify the normal and unusual of expression variations of the human face is proposed. The approach uses the binary edge image to present the shape of facial expression. The modified Hausdorff distance measure is adapted to our approach to compare between the unusual and normal face expression. In our algorithm, it just needs to use three face images per subject for training, which include two normal facial images and one unusual facial image to obtain individual thresholds for human face detection, respectively. Therefore, the proposed technique does not require a large number of images for training.
机译:在本文中,提出了一种简单的面部表情检测方法,以识别人脸的表达变化的正常和不寻常。该方法使用二进制边缘图像呈现面部表情的形状。修改后的Hausdorff距离测量适用于我们在不寻常和正常的面部表达之间进行比较的方法。在我们的算法中,只需要使用每个受试者的三个面部图像进行训练,其包括两个正常面部图像和一个不寻常的面部图像,以分别获得人脸检测的单个阈值。因此,所提出的技术不需要大量图像进行培训。

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