NOVEL AI BASED APPROACH FOR HUMAN BODY TEMPERATURE EVALUATION USING INNER EYE CANTHUS LOCALIZATION FROM CAMERA FEED

Rahul Kushwah, Rajiv Muradia, A. Bist
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Abstract

In this paper, we report development of an Artificial Intelligence (“AI”) based pipeline to localize inner canthus for human body temperature evaluation. Locating inner canthus in a camera feed remains a challenging endeavor. We have utilized numerous Facial points, nose points and eye landmarks to locate inner canthus and report four novel aspects of our work in evaluating human body temperature. Our first novelty lies in the process of locating ROI for correct observations. Our second novelty lies in solving the challenge of mapping RGB and Thermal images to get exact data points. Our third novelty lies in testing our algorithms/technology by developing automated testing pipelines on large datasets. Moreover, the fourth novel aspect of our work lies in our methodology to normalize the temperature from forehead, inner canthus & using our hardware configuration. We tested our algorithm with data comprising of different age groups, gender and geographical location and obtained 98.37% accuracy.
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基于人工智能的人眼内眦定位体温评估方法
在本文中,我们报告了一种基于人工智能(“AI”)的管道的开发,用于定位人体体温评估的内眼角。在摄像机馈送中定位内眼角仍然是一项具有挑战性的工作。我们利用许多面部点、鼻子点和眼睛标记来定位内眼角,并报告了我们在评估人体温度方面的四个新工作。我们的第一个新颖之处在于定位ROI以获得正确观测的过程。我们的第二个创新在于解决映射RGB和热图像以获得精确数据点的挑战。我们的第三个新奇之处在于通过在大型数据集上开发自动化测试管道来测试我们的算法/技术。此外,我们工作的第四个新颖方面在于我们的方法来标准化温度从额头,内眼角&使用我们的硬件配置。我们用不同年龄、性别和地理位置的数据测试了我们的算法,准确率达到了98.37%。
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