A Novel Multisupervised Coupled Metric Learning for Low-Resolution Face Matching
المؤلفون المشاركون
Fu, Guixia
Peng, Xiang
Zou, Guofeng
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-03-16
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
This paper presents a new multisupervised coupled metric learning (MS-CML) method for low-resolution face image matching.
While coupled metric learning has achieved good performance in degraded face recognition, most existing coupled metric learning methods only adopt the category label as supervision, which easily leads to changes in the distribution of samples in the coupled space.
And the accuracy of degraded image matching is seriously influenced by these changes.
To address this problem, we propose an MS-CML method to train the linear and nonlinear metric model, respectively, which can project the different resolution face pairs into the same latent feature space, under which the distance of each positive pair is reduced and that of each negative pair is enlarged.
In this work, we defined a novel multisupervised objective function, which consists of a main objective function and an auxiliary objective function.
The supervised information of the main objective function is the category label, which plays a major supervisory role.
The supervised information of the auxiliary objective function is the distribution relationship of the samples, which plays an auxiliary supervisory role.
Under the supervision of category label and distribution information, the learned model can better deal with the intraclass multimodal problem, and the features obtained in the coupled space are more easily matched correctly.
Experimental results on three different face datasets validate the efficacy of the proposed method.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zou, Guofeng& Fu, Guixia& Peng, Xiang. 2020. A Novel Multisupervised Coupled Metric Learning for Low-Resolution Face Matching. Advances in Multimedia،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1126699
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zou, Guofeng…[et al.]. A Novel Multisupervised Coupled Metric Learning for Low-Resolution Face Matching. Advances in Multimedia No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1126699
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zou, Guofeng& Fu, Guixia& Peng, Xiang. A Novel Multisupervised Coupled Metric Learning for Low-Resolution Face Matching. Advances in Multimedia. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1126699
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1126699
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر