一种有效的人脸检测算法

Zuzana Képešiová, S. Kozák
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引用次数: 5

摘要

本文研究了在线web应用的实时人脸检测问题及其解决方案。本文的主要目的是描述有效的人脸检测算法的功能,并分析现有的解决方案,以改善现状。为了获得满意的结果,我们选择了Viola-Jones目标检测框架,该框架将特征选择与Integral图像、AdaBoost训练和级联分类器相结合。该算法在现有的用于人脸或其他对象检测的javaScript框架中非常流行,因为它在实现高检测率和多对象检测的同时,具有极高的图像处理速度。作为解决上述问题的分析答案,选择了javaScript tracking.js。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An effective face detection algorithm
This paper studies a real-time face detection problem for online web applications and its solution. The main aim of this paper is describe functionality of effective face detection algorithm and analyze existing solution in order to improve current situation. To obtain satisfying results Viola-Jones object detection framework is chosen, which uses feature selection in combination with Integral images, AdaBoost training and Cascading classifiers. This algorithm is highly popular among existing javaScript frameworks for face or another objects detection for its extreme speed of image processing while achieving high detection rates and multiple objects detection. As analyzed answer for solving stated problem a javaScript tracking.js is chosen.
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