基于三维图像测量的直观人机交互头部姿态估计方法

Cheng Xul, Ying Kang, Kazuhiro Tsujino, Cunwei Lu
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引用次数: 0

摘要

人的头部姿态的实时检测在汽车安全驾驶、游戏和机器人人机界面等领域具有重要意义。针对驾驶员头部的姿态估计,已有一些技术,如利用眼睛瞳孔和虹膜的位置来检测视线,利用眼睛和鼻子之间的位置关系等。然而,在这些技术中存在一个问题,即图像测量结果受环境光和驾驶员面部化妆的影响。然后,它不能估计大范围的面部方向。为了解决这一问题,我们提出了一种基于红外模式投影技术的三维图像分析估计驾驶员头部姿态的技术。我们提出的技术包括两部分:一是驾驶员头部的三维图像测量,二是基于三维图像分析的头部姿态估计。作为三维图像测量方法,为了获得可靠的三维图像,我们采用了狭缝投影技术;为了保证近鼻部分的三维测量精度和三维测量速度,我们只使用三条条纹投影在脸上;为了减少外界光线对人体的影响,我们采用了红外模式投影。为了快速估计头部姿态,我们将人脸轮廓建模为线性逼近,然后利用人脸度与直线斜率之间的关系来判断人脸方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A head posture estimation method based on 3-D images measurement for intuitive human-system interaction
Real-time detection of the person's head posture is very important in field such as safe driving of automobile, man-machine interface of game and robot, and so on. Some techniques about the posture estimation of driver's head are existed, like detecting the sight line from the position of the pupil and iris of the eyes, using the positional relationship between the eyes and nose, and so on. However, there is a problem that the result of image measuring is influenced by ambient light and face makeup of the driver in these techniques. And then, it cannot estimate a wide range of face direction. In order to solve this problem, we propose a technique of estimate the head posture of the driver by three-dimensional (3-D) image analysis which is based on the infrared pattern projection technique. The technique we proposed includes two portions: one is 3-D image measurement of driver's head and the other is the head posture estimation by 3-D image analysis. As the 3-D image measurement method, in order to obtain a reliable 3-D image, we use slit pattern projection technique; in order to keep the 3-D measurement accurate of the portion near the nose, and the 3-D measurement speed, we only use three stripes to project on the face; in order to reduce the influence of external light on the people's body, we use infrared pattern projection. To estimate the head posture quickly, we face contour modeled as linear approximation, and then use the relationship between the face degree and the slope of the line to judge the face direction.
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