Living body recognition method based on facial feature point motion
A kind of living body recognition method was proposed,which was applied in mobile terminal and based on the deep learning.A facial movements LSTM network was trained using data sets.When users input a random sequence of video,user’s facial feature point data can be gained and whether the video forge...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2018-06-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2018044 |
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| _version_ | 1841530169008848896 |
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| author | Yulong WANG Kaiyuan LIU |
| author_facet | Yulong WANG Kaiyuan LIU |
| author_sort | Yulong WANG |
| collection | DOAJ |
| description | A kind of living body recognition method was proposed,which was applied in mobile terminal and based on the deep learning.A facial movements LSTM network was trained using data sets.When users input a random sequence of video,user’s facial feature point data can be gained and whether the video forgery attacks happened will be determined by input user’s facial feature point data into circulation neural network.The test data shows that the proposed method can be protected effectively from photograph attack and video replay attack. |
| format | Article |
| id | doaj-art-c8cb850cd2cd4076b46090ae194919a2 |
| institution | Kabale University |
| issn | 2096-109X |
| language | English |
| publishDate | 2018-06-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj-art-c8cb850cd2cd4076b46090ae194919a22025-01-15T03:12:51ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2018-06-014364459553521Living body recognition method based on facial feature point motionYulong WANGKaiyuan LIUA kind of living body recognition method was proposed,which was applied in mobile terminal and based on the deep learning.A facial movements LSTM network was trained using data sets.When users input a random sequence of video,user’s facial feature point data can be gained and whether the video forgery attacks happened will be determined by input user’s facial feature point data into circulation neural network.The test data shows that the proposed method can be protected effectively from photograph attack and video replay attack.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2018044living body recognitionfacial feature pointdeep learningLSTM |
| spellingShingle | Yulong WANG Kaiyuan LIU Living body recognition method based on facial feature point motion 网络与信息安全学报 living body recognition facial feature point deep learning LSTM |
| title | Living body recognition method based on facial feature point motion |
| title_full | Living body recognition method based on facial feature point motion |
| title_fullStr | Living body recognition method based on facial feature point motion |
| title_full_unstemmed | Living body recognition method based on facial feature point motion |
| title_short | Living body recognition method based on facial feature point motion |
| title_sort | living body recognition method based on facial feature point motion |
| topic | living body recognition facial feature point deep learning LSTM |
| url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2018044 |
| work_keys_str_mv | AT yulongwang livingbodyrecognitionmethodbasedonfacialfeaturepointmotion AT kaiyuanliu livingbodyrecognitionmethodbasedonfacialfeaturepointmotion |