论文标题
使用近红外IRIS图像序列的行为曲线分析
Behavioural Curves Analysis Using Near-Infrared-Iris Image Sequences
论文作者
论文摘要
本文提出了一种新的方法，以估算近乎infra-Red（NIR）虹膜视频帧的行为曲线。该方法可用于占空比健身系统（FFD）。该研究重点是确定外部因素（例如酒精，药物和嗜睡）对中枢神经系统（CNS）的影响。目的是分析这种行为在虹膜和学生运动上的表示，以及是否有可能使用标准的NIR相机捕获这些更改。行为分析表明，学生和虹膜行为的基本差异，以对工人在“拟合”或“不合适”条件下分类。最佳结果可以在酒精，吸毒和睡眠条件下牢固地区分受试者。在所有组中，多层play剂和梯度提升机在所有组中都取得了最佳效果，其合身性和不合适的级别分别为74.0％和75.5％。这些结果为虹膜捕获设备开了一个新的应用程序。
This paper proposes a new method to estimate behavioural curves from a stream of Near-Infra-Red (NIR) iris video frames. This method can be used in a Fitness For Duty system (FFD). The research focuses on determining the effect of external factors such as alcohol, drugs, and sleepiness on the Central Nervous System (CNS). The aim is to analyse how this behaviour is represented on iris and pupil movements and if it is possible to capture these changes with a standard NIR camera. The behaviour analysis showed essential differences in pupil and iris behaviour to classify the workers in "Fit" or "Unfit" conditions. The best results can distinguish subjects robustly under alcohol, drug consumption, and sleep conditions. The Multi-Layer-Perceptron and Gradient Boosted Machine reached the best results in all groups with an overall accuracy for Fit and Unfit classes of 74.0% and 75.5%, respectively. These results open a new application for iris capture devices.
