Patch Based Collaborative Representation with Gabor Feature and Measurement Matrix for Face Recognition
المؤلفون المشاركون
Ye, Mingquan
Liu, Yu
Xu, Zhengyuan
Huang, Lei
Yu, Hao
Chen, Xun
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-05-10
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
In recent years, sparse representation based classification (SRC) has emerged as a popular technique in face recognition.
Traditional SRC focuses on the role of the l1-norm but ignores the impact of collaborative representation (CR), which employs all the training examples over all the classes to represent a test sample.
Due to issues like expression, illumination, pose, and small sample size, face recognition still remains as a challenging problem.
In this paper, we proposed a patch based collaborative representation method for face recognition via Gabor feature and measurement matrix.
Using patch based collaborative representation, this method can solve the problem of the lack of accuracy for the linear representation of the small sample size.
Compared with holistic features, the multiscale and multidirection Gabor feature shows more robustness.
The usage of measurement matrix can reduce large data volume caused by Gabor feature.
The experimental results on several popular face databases including Extended Yale B, CMU_PIE, and LFW indicated that the proposed method is more competitive in robustness and accuracy than conventional SR and CR based methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Xu, Zhengyuan& Liu, Yu& Ye, Mingquan& Huang, Lei& Yu, Hao& Chen, Xun. 2018. Patch Based Collaborative Representation with Gabor Feature and Measurement Matrix for Face Recognition. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1206587
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Xu, Zhengyuan…[et al.]. Patch Based Collaborative Representation with Gabor Feature and Measurement Matrix for Face Recognition. Mathematical Problems in Engineering No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1206587
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Xu, Zhengyuan& Liu, Yu& Ye, Mingquan& Huang, Lei& Yu, Hao& Chen, Xun. Patch Based Collaborative Representation with Gabor Feature and Measurement Matrix for Face Recognition. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1206587
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1206587
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