Inner Eye Canthus Localization for Human Body Temperature Screening
| Autor: | Lorenzo Berlincioni, Marco Bertini, Alberto Del Bimbo, Claudio Ferrari |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Biometrics business.industry Computer science Computer Vision and Pattern Recognition (cs.CV) 020208 electrical & electronic engineering Visibility (geometry) Computer Science - Computer Vision and Pattern Recognition Body temperature measurement 02 engineering and technology Solid modeling Thermal Imaging BioMetrics Temperature Screening Computer Vision Face model Face (geometry) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Canthus Computer vision Artificial intelligence business Projection (set theory) |
| Zdroj: | ICPR |
| DOI: | 10.1109/icpr48806.2021.9412015 |
| Popis: | 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/. |
| Databáze: | OpenAIRE |
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