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dc.contributor.advisor金泰松
dc.contributor.author刘志凌
dc.date.accessioned2018-12-05T01:47:52Z
dc.date.available2018-12-05T01:47:52Z
dc.date.issued2018-01-02
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/170507
dc.description.abstract人脸图像分析是一个具有重要理论意义和应用价值的研究方向。如何提取人脸图像特征、实现算法模型并在图像分析过程中获得更加高效、鲁棒的结果,吸引了模式识别、图像处理、计算机视觉、人工智能和神经网络等多个领域的众多学者对其进行研究。本文以人脸为研究对象,重点研究基于流形保持方法的图像特征提取与识别问题。主要工作如下: (1)基于流形保持的人脸图像聚类方法的研究。使用含有干扰信息的人脸图像集作为实验数据集,包含人脸的光照条件变化、遮挡情况变化、面部表情变化、样本数目变化以及随机像素点噪声等干扰因素。选取十种使用邻接图保持局部性的人脸图像分析方法进行聚类分析实验,根据实验结果,探究人脸图像干扰因素对流形...
dc.description.abstractAutomatic facial image analysis has very large theoretic and practical values. How to extract facial features, implement the algorithm and obtain more efficient results through facial image analysis and recognition, is attracting a large number of researchers to study from multiple fields such as pattern recognition, computer vision, artificial intelligence and neural network. This thesis focuses ...
dc.language.isozh_CN
dc.relation.urihttps://catalog.xmu.edu.cn/opac/openlink.php?strText=58826&doctype=ALL&strSearchType=callno
dc.source.urihttps://etd.xmu.edu.cn/detail.asp?serial=60218
dc.subject人脸图像分析
dc.subject流形学习
dc.subject局部保持
dc.subjectFacial image analysis
dc.subjectLocality preserving
dc.subjectManifold learning
dc.title流形保持的人脸图像分析方法研究
dc.title.alternativeAutomatic Facial Image Analysis based on Locality Preserving
dc.typethesis
dc.date.replied2017-05-17
dc.description.note学位:工程硕士
dc.description.note院系专业:信息科学与技术学院_工程硕士(计算机技术)
dc.description.note学号:23020141153184


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