基于随机森林的人脸特征检测方法研究

Research on face feature detection based on random forest

在计算机视觉中,人脸特征检测是一个非常关键的问题,是进行人脸识别、人脸跟踪和表情识别等的基础。在许多专业领域,如人机互动、军用分析等,都有很大的发展空间。脸部特征量侦测的目的在于迅速且精确地从脸部影像中找出脸部特征量(例如:眉毛,眼睛,鼻子,口部等)的定位,为进一步了解面孔信息提供依据。近几年,随着物联网技术的迅速发展和国际学者们对面部识别问题的不断探索,面部识别问题已经有了很大程度的进展。然而,因为面部图像的复杂性和面部姿势的多样化特征,使得面部特征检测在实时性、准确性方面仍有很大的提升空间。文章主要对一种应用随机森林进行面部特征提取的算法进行讨论和总结。

In computer vision,facial feature detection is a crucial issue,which is the foundation for facial recognition,facial tracking,and expression recognition.In many professional fields,such as human-computer interaction and military analysis,there is great room for development.The purpose of facial feature detection is to quickly and accurately locate facial features(such as eyebrows,eyes,nose,mouth,etc.)from facial images,providing a foundation for further understanding facial information.In recent years,with the rapid development of the Internet of Things technology and the continuous exploration of facial recognition problems by international scholars,the problem of facial recognition has made significant progress.However,due to the complexity of facial images and the diverse features of facial poses,there is still great room for improvement in real-time and accuracy of facial feature detection.This paper mainly discusses and summarizes an algorithm of facial feature extraction using random forest.