论文标题
以眼睛注视贝尔在视频中的麻痹的检测
Eye-focused Detection of Bell's Palsy in Videos
论文作者
论文摘要
在本文中，我们介绍了贝尔的麻痹是一种神经系统疾病，在视频中只能从受试者的眼睛中检测到。我们注意到贝尔的麻痹患者经常难以眨眼在受影响的一面。结果，我们可以观察到两只眼睛的闪烁模式之间存在明显的对比。尽管以前的作品确实利用了图像/视频来检测这种疾病，但没有一个明确专注于眼睛。他们中的大多数都需要整个脸。具有引人注目的检测系统的一个明显优势是受试者的匿名性没有风险。同样，我们基于简单闪烁模式的AI决定使它们可以解释且直接。具体而言，我们开发了一个名为Blink相似性的新颖功能，该功能衡量了两个闪烁模式之间的相似性。我们的广泛实验表明，所提出的功能非常健壮，因为即使标签很少，它也有助于贝尔的麻痹检测。我们提出的以眼睛为中心的检测系统不仅比现有方法便宜，而且更方便。
In this paper, we present how Bell's Palsy, a neurological disorder, can be detected just from a subject's eyes in a video. We notice that Bell's Palsy patients often struggle to blink their eyes on the affected side. As a result, we can observe a clear contrast between the blinking patterns of the two eyes. Although previous works did utilize images/videos to detect this disorder, none have explicitly focused on the eyes. Most of them require the entire face. One obvious advantage of having an eye-focused detection system is that subjects' anonymity is not at risk. Also, our AI decisions based on simple blinking patterns make them explainable and straightforward. Specifically, we develop a novel feature called blink similarity, which measures the similarity between the two blinking patterns. Our extensive experiments demonstrate that the proposed feature is quite robust, for it helps in Bell's Palsy detection even with very few labels. Our proposed eye-focused detection system is not only cheaper but also more convenient than several existing methods.
