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Yawn analysis with mouth occlusion detection

机译:打哈欠分析与嘴巴遮挡检测

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摘要

One of the most common signs of tiredness or fatigue is yawning. Naturally, identification of fatigued individuals would be helped if yawning is detected. Existing techniques for yawn detection are centred on measuring the mouth opening. This approach, however, may fail if the mouth is occluded by the hand, as it is frequently the case. The work presented in this paper focuses on a technique to detect yawning whilst also allowing for cases of occlusion. For measuring the mouth opening, a new technique which applies adaptive colour region is introduced. For detecting yawning whilst the mouth is occluded, local binary pattern (LBP) features are used to also identify facial distortions during yawning. In this research, the Strathclyde Facial Fatigue (SFF) database which contains genuine video footage of fatigued individuals is used for training, testing and evaluation of the system. (C) 2015 Elsevier Ltd. All rights reserved.
机译:打哈欠是最常见的疲倦或疲劳迹象之一。自然,如果检测到打呵欠,将有助于识别疲劳的人。现有的哈欠检测技术集中在测量张口。但是,如果经常用手堵塞嘴部,则该方法可能会失败。本文介绍的工作重点是在检测打哈欠的同时还允许遮挡的技术。为了测量张口,介绍了一种应用自适应颜色区域的新技术。为了在咬嘴时检测到打哈欠,使用局部二进制模式(LBP)功能还可以识别打哈欠期间的面部变形。在这项研究中,斯特拉斯克莱德面部疲劳(SFF)数据库包含了疲劳个体的真实视频录像,用于系统的培训,测试和评估。 (C)2015 Elsevier Ltd.保留所有权利。

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