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Inner Eye Canthus Localization for Human Body Temperature Screening

机译:人体温度筛选的内眼晕士本地化

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In this paper, we propose an automatic approach for localizing the inner eye canthus in thermal face images. We first coarsely detect 5 facial keypoints corresponding to the center of the eyes, the nosetip and the ears. Then we compute a sparse 2D-3D points correspondence using a 3D Morphable Face Model (3DMM). This correspondence is used to project the entire 3D face onto the image, and subsequently locate the inner eye canthus. Detecting this location allows to obtain the most precise body temperature measurement for a person using a thermal camera. We evaluated the approach on a thermal face dataset provided with manually annotated landmarks. However, such manual annotations are normally conceived to identify facial parts such as eyes, nose and mouth, and are not specifically tailored for localizing the eye canthus region. As additional contribution, we enrich the original dataset by using the annotated landmarks to deform and project the 3DMM onto the images. Then, by manually selecting a small region corresponding to the eye canthus, we enrich the dataset with additional annotations. By using the manual landmarks, we ensure the correctness of the 3DMM projection, which can be used as ground-truth for future evaluations. Moreover, we supply the dataset with the 3D head poses and per-point visibility masks for detecting self-occlusions. The data is publicly available at https://www.micc.unifi.it/resources/datasets/thermal-face/.
机译:在本文中,我们提出了一种自动方法,用于定位热面图像中的内眼晕座。我们首先粗略地检测对应于眼睛的中心的5个面部关键点,镍胶和耳朵。然后,我们使用3D可变面部模型(3DMM)计算稀疏的2D-3D点对应关系。这种对应关系用于将整个3D面向图像投影到图像上,随后定位内眼晕圈。检测该位置允许使用热摄像头获得人的最精确的体温测量。我们在提供手动注释的地标的热面部数据集中评估了这种方法。然而,通常设想这样的手动注释,以识别眼睛,鼻子和嘴巴等面部部件,并且没有特别定制用于本地化眼睛角落区域。作为额外贡献,我们通过使用注释的地标更改原始数据集以使3DMM变形并将3DMM投影到图像上。然后,通过手动选择对应于眼角的小区域,我们通过附加注释来丰富数据集。通过使用手动标志性标志,我们确保3DMM投影的正确性,这可以用作未来评估的地面真理。此外,我们使用3D头部姿势和每点可见性掩模来提供用于检测自闭锁的数据集。数据在https://www.micc.unifi.it/resources/datasets/thermal -face/上公开可用。

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