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

机译:一种实时眉的分割和跟踪技术,支持电动轮椅界面

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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:本文介绍了一种眉毛跟踪方法,用于支持电动轮椅的界面。该界面旨在通过解释头部和面部特征的移动,而无需生成的命令,旨在通过解释轮椅。控制接口的硬件由带连接到其的网络摄像机的头盔组成:相机指向用户的面部,并且实时获取和处理图像序列。本文侧重于眉毛运动给出的命令的解释。在检测眼区域之后,眉毛由CIELAB色彩空间L和B带的组成分段,通过经典OTSU阈值合成二值化。跟踪通过计算和分析垂直位签名,从分段眉提取。移动和停止命令的产生产生了令人满意的结果。眉毛跟踪表明,在纵横化和不同的光线条件和用户肤色中是准确和稳健的。

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