Head-pose estimation plays an important role in computer vision. The head-pose estimation aims to determine the orientation of a human head by representing the yaw, pitch, and roll angles. Implementations can be achieved by different techniques depending on the type of input and training data. This article presents a simple three-dimensional (3-D) face model for estimating head poses. The personalized 3-D face model is constructed by 2-D face photographs. A frontal face photograph determines the plane coordinates of facial features. By knowing the yaw angles in the other averted face photograph, the depth coordinates can be determined. The yaw angle of the averted face is evaluated by the canthus positions. Once the 3-D face model is constructed, we can find the matching angles for a target head pose in a query 2-D photograph. The personalized 3-D face model rotates itself about the x -, y -, and z -axes and then projects its facial features onto plane coordinates. If the rotation angles are correct, the disparities between the 2-D facial features and those in the query face photograph are supposed to be at their minimum. The personalized 3-D face model is validated with the University of South Florida human-identification database. The performance of the proposed head-pose estimation is evaluated on the Biwi Kinect head-pose database and Pointing’04 head-pose image database. The results show that the proposed method outperforms state-of-the-art technologies on both benchmark databases.

中文翻译：

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二维图像中基于外眦定位的头部姿势估计

头部姿势估计在计算机视觉中起着重要作用。头部姿势估计旨在通过表示偏航角、俯仰角和滚动角来确定人体头部的方向。根据输入和训练数据的类型，可以通过不同的技术来实现。本文介绍了一个用于估计头部姿势的简单三维 (3-D) 面部模型。个性化3D人脸模型是由2D人脸照片构建的。正面照片决定了面部特征的平面坐标。通过知道另一张避开的脸部照片中的偏航角，可以确定深度坐标。通过眼角位置来评估避开的脸部的偏航角。一旦构建了 3D 人脸模型，我们就可以在查询的 2D 照片中找到目标头部姿势的匹配角度。个性化 3D 脸部模型围绕X -，y - 和z 轴，然后将其面部特征投影到平面坐标上。如果旋转角度正确，则二维面部特征与查询面部照片中的面部特征之间的差异应该是最小的。个性化 3D 面部模型经过南佛罗里达大学人类识别数据库的验证。所提出的头部姿势估计的性能在 Biwi Kinect 头部姿势数据库和 Pointing'04 头部姿势图像数据库上进行了评估。结果表明，所提出的方法在两个基准数据库上都优于最先进的技术。