کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6938833 | 1449966 | 2018 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Robust, discriminative and comprehensive dictionary learning for face recognition
ترجمه فارسی عنوان
یادگیری فرهنگ لغت، محرمانه و جامع برای تشخیص چهره
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کلمات کلیدی
یادگیری فرهنگ لغت تشخیص چهره، نمایندگی انحصاری،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
For sparse representation or sparse coding based image classification, the dictionary, which is required to faithfully and robustly represent query images, plays an important role on its success. Learning dictionaries from the training data for sparse coding has shown state-of-the-art results in image classification and face recognition. However, for face recognition, conventional dictionary learning methods cannot well learn a reliable and robust dictionary due to suffering from the small-sample-size problem. The other significant issue is that current dictionary learning do not completely cover the important components of signal representation (e.g., commonality, particularity, and disturbance), which limit their performance. In order to solve the above issues, in this paper, we propose a novel robust, discriminative and comprehensive dictionary learning (RDCDL) method, in which a robust dictionary is learned from comprehensive training sample diversities generated by extracting and generating facial variations. Especially, to completely represent the commonality, particularity and disturbance, class-shared, class-specific and disturbance dictionary atoms are learned to represent the data from different classes. Discriminative regularizations on the dictionary and the representation coefficients are used to exploit discriminative information, which effectively improves the classification capability of the dictionary. The proposed RDCDL method is extensively evaluated on benchmark face image databases, and it shows superior performance to many state-of-the-art dictionary learning methods for face recognition.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 81, September 2018, Pages 341-356
Journal: Pattern Recognition - Volume 81, September 2018, Pages 341-356
نویسندگان
Guojun Lin, Meng Yang, Jian Yang, Linlin Shen, Weicheng Xie,