Face recognition under unconstrained based on LBP and deep learning
A face recognition method under unconstrained condition was proposed based on deep learning. At the same time, making LBP texture features as the input of deep learning net, and greedy training the network layer was made by layer to obtain good network parameters. At last, the trained net was used t...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2014-06-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.06.020/ |
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| _version_ | 1841539771028996096 |
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| author | Shu-fen LIANG Yin-hua LIU Li-chen LI |
| author_facet | Shu-fen LIANG Yin-hua LIU Li-chen LI |
| author_sort | Shu-fen LIANG |
| collection | DOAJ |
| description | A face recognition method under unconstrained condition was proposed based on deep learning. At the same time, making LBP texture features as the input of deep learning net, and greedy training the network layer was made by layer to obtain good network parameters. At last, the trained net was used to predict the test samples' labels. The results of experiments on LFW(labeled faces in the wild) show that the algorithm can obtain higher recognition rate than traditional algorithms(such as PCA, SVM, LBP).Otherwise, the recognition rate on Yale and Yale-B are also very high, the experi-mental results show that deep learning net with LBP texture as its input can classify face images correctly. |
| format | Article |
| id | doaj-art-e1272f343a954276be1fb320f00d1cf9 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2014-06-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-e1272f343a954276be1fb320f00d1cf92025-01-14T06:43:37ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2014-06-013515416059682259Face recognition under unconstrained based on LBP and deep learningShu-fen LIANGYin-hua LIULi-chen LIA face recognition method under unconstrained condition was proposed based on deep learning. At the same time, making LBP texture features as the input of deep learning net, and greedy training the network layer was made by layer to obtain good network parameters. At last, the trained net was used to predict the test samples' labels. The results of experiments on LFW(labeled faces in the wild) show that the algorithm can obtain higher recognition rate than traditional algorithms(such as PCA, SVM, LBP).Otherwise, the recognition rate on Yale and Yale-B are also very high, the experi-mental results show that deep learning net with LBP texture as its input can classify face images correctly.http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.06.020/unconstrained conditionface recognitionLBPdeep networkdeep learning |
| spellingShingle | Shu-fen LIANG Yin-hua LIU Li-chen LI Face recognition under unconstrained based on LBP and deep learning Tongxin xuebao unconstrained condition face recognition LBP deep network deep learning |
| title | Face recognition under unconstrained based on LBP and deep learning |
| title_full | Face recognition under unconstrained based on LBP and deep learning |
| title_fullStr | Face recognition under unconstrained based on LBP and deep learning |
| title_full_unstemmed | Face recognition under unconstrained based on LBP and deep learning |
| title_short | Face recognition under unconstrained based on LBP and deep learning |
| title_sort | face recognition under unconstrained based on lbp and deep learning |
| topic | unconstrained condition face recognition LBP deep network deep learning |
| url | http://www.joconline.com.cn/zh/article/doi/10.3969/j.issn.1000-436x.2014.06.020/ |
| work_keys_str_mv | AT shufenliang facerecognitionunderunconstrainedbasedonlbpanddeeplearning AT yinhualiu facerecognitionunderunconstrainedbasedonlbpanddeeplearning AT lichenli facerecognitionunderunconstrainedbasedonlbpanddeeplearning |