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Extraction of Eye and Mouth Features for Drowsiness Face Detection Using Neural Network

机译：基于神经网络的睡意人脸特征提取眼与嘴特征

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摘要

Facial feature extraction is the process of searching for features of facial components such as eyes, nose, mouth and other parts of human facial features. Facial feature extraction is essential for initializing processing techniques such as face tracking, facial expression recognition or face shape recognition. Among all facial features, eye area detection is important because of the detection and localization of the eye. The location of all other facial features can be identified. This study describes automated algorithms for feature extraction of eyes and mouth. The data takes form of video, then converted into a sequence of images through frame extraction process. From the sequence of images, feature extraction is based on the morphology of the eyes and mouth using Neural Network Backpropagation method. After feature extraction of the eye and mouth is completed, the result of the feature extraction will later be used to detect a person’s drowsiness, being useful for other research.
机译：面部特征提取是搜索面部组件（例如眼睛，鼻子，嘴巴和人类面部特征的其他部分）的特征的过程。面部特征提取对于初始化诸如面部跟踪，面部表情识别或面部形状识别之类的处理技术至关重要。在所有面部特征中，由于眼睛的检测和定位，眼睛区域检测非常重要。可以识别所有其他面部特征的位置。这项研究描述了用于眼睛和嘴巴的特征提取的自动算法。数据采用视频形式，然后通过帧提取过程转换为一系列图像。从图像序列中，使用神经网络反向传播方法基于眼睛和嘴巴的形态提取特征。眼睛和嘴巴的特征提取完成后，特征提取的结果将稍后用于检测人的嗜睡情况，这对其他研究很有用。

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