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首页> 外文会议>2016 World Conference on Futuristic Trends in Research and Innovation for Social Welfare >Occlusion invariant face recognition system
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Occlusion invariant face recognition system

机译：遮挡不变人脸识别系统

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Face recognition has acquired a lot of attention in market and research communities, but still remained very accosting in real time applications. It is one of the several techniques used for identifying an individual. In face recognition system there are many factors which affect the performance of a system. The major factors affecting the face recognition system are pose, illumination, ageing, occlusion and expression etc. Among the above mentioned problem an occlusion is most affecting problem in face recognition. In a face recognition system due to obstacles like sunglasses, scarf etc. we cannot recognize a face image. So first we detect an occlusion from a face image by using a SVM (Support Vector Machine) classifier. To resolve the occlusion problem, each face is divided into k local regions which are analyzed in isolation. We discard an occluded part in a face image and based on remaining non-occluded part of a face image we will recognize a face image. For face recognition purpose we will be using a near set theory.
机译：人脸识别已在市场和研究界引起了广泛关注，但在实时应用中仍然非常抢手。它是用于识别个人的几种技术之一。在人脸识别系统中，有许多因素会影响系统的性能。影响面部识别系统的主要因素是姿势，照明，老化，遮挡和表情等。在上述问题中，遮挡是面部识别中影响最大的问题。在人脸识别系统中，由于太阳镜，围巾等障碍物，我们无法识别人脸图像。因此，首先，我们使用SVM（支持向量机）分类器从面部图像中检测出遮挡。为了解决遮挡问题，将每个人脸分为k个局部区域，并对其进行隔离分析。我们丢弃面部图像中被遮挡的部分，并基于面部图像的剩余未被遮挡的部分，我们将识别出面部图像。出于面部识别的目的，我们将使用近似集理论。

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