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Person Recognition Using Surf Features and Vola-Jones Algorithm

机译:使用冲浪功能和Vola-Jones算法的人员识别

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摘要

Face recognition is one of the prominent biometric software applications, which can identify specific person in a digital image by analysing few parameters and comparing them. These type of recognitions are commonly used in security systems but are used increasingly in variety of other applications. Few non static conditions like facial hair can make recognition system a serious problem. The three stages of face recognition system are facing detection, feature extraction and classification. For enhancing the face recognition from video successions against dissimilar occlusion invariant and posture is proposed by using a novel approach. This face identification system made use of Viola and Jones algorithm for face detection and SURF (Speed Up Robust Feature) for feature extraction. Classifications of these face images are done using RBF (Radial Basis Function kernel) SVM (Support Vector Machine) classifier.
机译:面部识别是突出的生物识别软件应用之一,可以通过分析少数参数并进行比较来识别数字图像中的特定人。这些类型的识别通常用于安全系统中,但越来越多地用于其他应用程序。少量非静态条件像面部发毛可以使识别系统成为一个严重的问题。面部识别系统的三个阶段面临检测,特征提取和分类。为了提高对不同遮挡不变的识别识别,通过使用一种新方法提出了姿势和姿势。这种脸部识别系统利用Viola和Jones算法进行面部检测和冲浪(加速鲁棒功能),用于特征提取。使用RBF(径向基函数内核)SVM(支持向量机)分类器进行这些面部图像的分类。

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