基于机器学习和开放CV分类器的人脸检测

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引用次数: 2

摘要

在过去的几年里,人脸识别在图像评估和识别领域占有相当大的地位,并且是最常用的功能之一。人脸检测反映了对人脸注意操作的一个不可思议的部分的考虑。基于像素的人脸检测技术是一种复杂的人脸检测技术,它提供了人脸的许多特征的可变性。面部包括姿势、表情、微笑、角色和方向、毛孔和肤色、是否戴眼镜或面部毛发、数码相机增益的变化、照明条件和照片分辨率。哈尔级联分类器在顺利完成这项任务时提供了出色的帮助。人脸检测在人脸检测领域占有举足轻重的地位,因此,熟悉它的功能,如借助摄像头的考勤系统,面具检测系统。在本文中,我们提出了一个利用计算机学习,特别是OpenCV的人脸检测系统。所需的强制步骤是人脸检测,我们使用了一个广泛使用的步骤,称为haarcascade_frontalface_default分类器,python及其模块。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Face Detection with Machine Learning and Open CV Classifier
In the last few years, face recognitions owned considerable consideration and liked together of the foremost used functions within the area of image evaluation and recognition. Face detection reflects on consideration of an incredible section of face attention operations. The technique of face detection in pixels is elaborate with many features’ variabilities provided throughout human faces. Faces include pose, expression, smile, role and orientation, pores and complexion, the presence of glasses or facial hair, variations in digicam gain, lighting conditions, and photo resolutions. Haar Cascade classifier is of outstanding assist when performing this undertaking smoothly. Face detection goes to possess a dramatic impression on the face detection field, as a result, familiarizing yourself with its functions like attendance recording system with the help of camera, Mask detection system. In this paper, we proposed a face detection system for the utilization of computer learning, especially OpenCV. The mandatory step required is face detection which we did with the usage of a broadly used step referred to as the haarcascade_frontalface_default classifier, python and its module.
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