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头部屈曲检测在增强眼睛注视方向分类中的应用。

Application of head flexion detection for enhancing eye gaze direction classification.

作者信息

Al-Rahayfeh Amer, Faezipour Miad

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:966-9. doi: 10.1109/EMBC.2014.6943753.

Abstract

Extensive research has been conducted on the tracking and detection of the eye gaze and head movement detection as these aspects of technology can be applied as alternative approaches for various interfacing devices. This paper proposes enhancements to the classification of the eye gaze direction. Viola Jones face detector is applied to first declare the region of the eye. Circular Hough Transform is then used to detect the iris location. Support Vector Machine (SVM) is applied to classify the eye gaze direction. Accuracy of the system is enhanced by calculating the flexion angle of the head through the utilization of a microcontroller and flex sensors. In case of rotated face images, the face can be rotated back to zero degrees through the flexion angle calculation. This is while Viola Jones face detector is limited to face images with very little or no rotation angle. Accuracy is initiated by enhancing the effectiveness of the system in the overall procedure of classifying the direction of the eye gaze. Therefore, the head direction is a main determinant in enhancing the control method. Different control signals are enhanced by the eye gaze direction classification and the head direction detection.

摘要

针对眼睛注视和头部运动检测的跟踪与检测已经开展了广泛研究,因为这些技术方面可作为各种接口设备的替代方法。本文提出了对眼睛注视方向分类的改进。首先应用Viola Jones面部检测器来确定眼睛区域。然后使用圆形霍夫变换来检测虹膜位置。支持向量机(SVM)用于对眼睛注视方向进行分类。通过利用微控制器和柔性传感器计算头部的弯曲角度,提高了系统的准确性。对于旋转的面部图像,可通过弯曲角度计算将面部旋转回零度。而Viola Jones面部检测器仅限于旋转角度很小或没有旋转角度的面部图像。通过提高系统在眼睛注视方向分类的整个过程中的有效性来提高准确性。因此,头部方向是增强控制方法的主要决定因素。眼睛注视方向分类和头部方向检测增强了不同的控制信号。

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