基于三维模型的Android手机端人脸姿态实时估计系统  

Real-time face pose estimation system based on 3D face model on Android mobile platform

作　　者：王海鹏[1] 王正良[2] 许威威[1] 范然[1] 

机构地区：[1]杭州师范大学杭州国际服务工程学院,杭州311121 [2]浙江省科技信息研究院信息资源中心,杭州311121

出　　处：《计算机应用》2015年第8期2321-2326,共6页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61322204;61272392)

摘　　要：针对人脸姿态估计对系统性能要求高、在手机上运行无法满足实时性要求等问题,实现了一种Android手机端的人脸姿态实时估计系统。首先,由摄像头获得一幅正面和一幅偏移一定角度的人脸图像,利用从运动中构建结构(Sf M)算法建立简单三维人脸模型;然后,提取实时人脸图像中与三维人脸模型相互对应的特征点,基于缩放正投影位姿估计(POSIT)算法估计人脸姿态角度;最后将三维人脸模型通过开放图形开发库(Open GL)实时显示在手机屏幕上。实验结果表明,实时视频中检测人脸姿态并显示的速度可以达到20 frame/s,接近计算机端的基于仿射对应的三维人脸姿态估计算法,而且针对大量图片序列的检测可以达到50 frame/s,能够满足Android手机端的性能和检测人脸姿态的实时性要求。Concerning that the high performance requirement of face pose estimation system which could not run on mobile phone in real time, a real-time face pose estimation system was realized for Android mobile phone terminals. First of all, one positive face image and one face image with a certain offset angle were obtained by the camera for establishing a simple 3D face model by Structure from Motion（ Sf M） algorithm. Secondly, the system extracted corresponding feature points from the real-time face image to 3D face model. The 3D face pose parameters were got by POSIT（ Pose from Orthography and Scaling with ITeration） algorithm. At last, the 3D face model was displayed on Android mobile terminals in real-time using Open GL（ Open Graphics Library）. The experimental results showed that the speed of detecting and displaying the face pose was up to 20 frame / s in the real-time video, which is close to 3D face pose estimation algorithm based on the affine correspondance on computer terminals; and the speed of detecting a large number of image sequences reached 50 frame / s. The results indicate that the system can satisfy the performance requirement for Android mobile phone terminals and real-time requirement of detecting the face pose.

关 键 词：人脸姿态 从运动中构建结构算法 显示形状回归 基于缩放正投影位姿估计 随机抽样一致算法 ANDROID 增强现实 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]