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A real-time eyebrow segmentation and tracking technique to support an electric wheelchair interface

机译:支持电动轮椅接口的实时眉毛分割和跟踪技术

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This paper presents an eyebrow tracking method to support an interface for an electric wheelchair. This interface aims to drive a wheelchair by interpreting the movement of the head and the facial features as well, without hand generated commands. Hardware for the control interface is composed by the helmet with a webcam attached to it: the camera is pointed to the face of the user and the image sequence is acquired and processed in real-time. This paper focuses on the interpretation of commands given by the eyebrows movements. Following the detection of the eyes regions, eyebrows are segmented by a composition of the CIELab colorspace L and b bands, binarized by the classical Otsu thresholding. Tracking is done by computation and analysis of the vertical bit signature, extracted from the segmented eyebrow. The generation of move and stop commands have produced satisfactory results. The eyebrow tracking demonstrated to be accurate and robust in trepidation and different light conditions and users skin tones.
机译:本文提出了一种支持电动轮椅接口的眉毛跟踪方法。该界面旨在通过解释头部和面部特征的运动来驱动轮椅,而无需人工生成命令。控制接口的硬件由连接有网络摄像头的头盔组成:将摄像头对准用户的面部,并实时获取和处理图像序列。本文着重于对眉毛运动指令的解释。在检测到眼睛区域之后,眉毛通过CIELab颜色空间L和b带的组成进行分割,并通过经典的Otsu阈值进行二值化。跟踪是通过计算和分析从分段眉毛中提取的垂直位签名来完成的。移动和停止命令的生成已产生令人满意的结果。眉毛追踪显示在颤抖和不同光线条件下以及使用者的肤色方面准确而坚固。

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