人脸和人脸特征检测

Monali V. Choudhari, M. S. Devi, P. Bajaj
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引用次数: 3

摘要

人脸检测涉及到在给定图像中找到每个人脸的位置和大小。在人物出现的图像或视频序列中定位皮肤像素有许多应用,特别是与人机交互相关的应用。人脸检测在人机交互领域起着非常重要的作用。它代表了全自动人脸识别、面部特征检测和表情识别的第一步。人脸检测中使用了许多技术,每种技术都有其优点和缺点。提出了一种改进光照条件下肤色模型人脸检测和人眼检测性能的算法。使用一组基于从训练集获得的肤色分布的边界规则提取皮肤区域。在对人脸区域进行检测后,利用霍夫变换对人脸特征即眼睛进行检测,特别是利用圆形霍夫变换对图像中的圆形物体进行检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Face and facial feature detection
Human face detection is concerned with finding location and size of every human face in a given image. Locating skin pixels in images or video sequences where people appear has many applications, especially those related to Human-Computer Interaction. Face detection plays a very important role in human computer interaction field. It represents the first step in a fully automatic face recognition, facial features detection, and expression recognition. There are many techniques used in face detection, each one has its advantages and disadvantages. An algorithm is proposed to improve the performance of face detection and eye detection using skin color model under poor illumination condition. Skin regions are extracted using a set of bounding rules based on the skin color distribution obtained from a training set. After detecting the face region, the Hough transform is used in order to detect the facial feature i. e. eye, specially circular Hough transform is used in order to detect the circular object in the image.
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