Research on professional talent training technology based on multimedia remote image analysis
Abstract In distance vocational education, teachers need to analyze according to the expression status of different students, so as to make corresponding training in training to improve training efficiency. At present, there are certain problems in the remote expression recognition of professional p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2019-02-01
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| Series: | EURASIP Journal on Image and Video Processing |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13640-019-0437-4 |
| _version_ | 1828764952953880576 |
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| author | Bin Xu Xiyuan Li Hao Liang Yuan Li |
| author_facet | Bin Xu Xiyuan Li Hao Liang Yuan Li |
| author_sort | Bin Xu |
| collection | DOAJ |
| description | Abstract In distance vocational education, teachers need to analyze according to the expression status of different students, so as to make corresponding training in training to improve training efficiency. At present, there are certain problems in the remote expression recognition of professional personnel. Based on this, this study analyzes the facial expression image and uses the wavelet transform algorithm to process the face image in complex lighting environment, thus improving the online transmission effect of the image. After that, this study uses orthogonal projection algorithm for face recognition. In addition, this paper enhances LBP features by dividing the original image into four images by wavelet decomposition. At the same time, in order to prevent the over-characteristics from reducing the classification accuracy and real-time calculation, this paper uses the PCA principal component analysis method to select the feature subset with the largest discrimination. Finally, through SVM, this article has done experiments on JAFFE facial expression database. The experimental results show that the proposed method has a significant improvement in the correct rate compared with the traditional LBP feature classification method and can improve the theoretical reference for subsequent related research. |
| first_indexed | 2024-12-11T06:40:02Z |
| format | Article |
| id | doaj.art-e0797dc467e4473abb62dbaa4dee9f8d |
| institution | Directory Open Access Journal |
| issn | 1687-5281 |
| language | English |
| last_indexed | 2024-12-11T06:40:02Z |
| publishDate | 2019-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Image and Video Processing |
| spelling | doaj.art-e0797dc467e4473abb62dbaa4dee9f8d2022-12-22T01:17:15ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-52812019-02-01201911910.1186/s13640-019-0437-4Research on professional talent training technology based on multimedia remote image analysisBin Xu0Xiyuan Li1Hao Liang2Yuan Li3Economics and Management School of Wuhan UniversityEconomics and Management School of Wuhan UniversityEconomics and Management School of Wuhan UniversityEconomics and Management School of Wuhan UniversityAbstract In distance vocational education, teachers need to analyze according to the expression status of different students, so as to make corresponding training in training to improve training efficiency. At present, there are certain problems in the remote expression recognition of professional personnel. Based on this, this study analyzes the facial expression image and uses the wavelet transform algorithm to process the face image in complex lighting environment, thus improving the online transmission effect of the image. After that, this study uses orthogonal projection algorithm for face recognition. In addition, this paper enhances LBP features by dividing the original image into four images by wavelet decomposition. At the same time, in order to prevent the over-characteristics from reducing the classification accuracy and real-time calculation, this paper uses the PCA principal component analysis method to select the feature subset with the largest discrimination. Finally, through SVM, this article has done experiments on JAFFE facial expression database. The experimental results show that the proposed method has a significant improvement in the correct rate compared with the traditional LBP feature classification method and can improve the theoretical reference for subsequent related research.http://link.springer.com/article/10.1186/s13640-019-0437-4MultimediaDistance learningProfessional talentTrainingImage |
| spellingShingle | Bin Xu Xiyuan Li Hao Liang Yuan Li Research on professional talent training technology based on multimedia remote image analysis EURASIP Journal on Image and Video Processing Multimedia Distance learning Professional talent Training Image |
| title | Research on professional talent training technology based on multimedia remote image analysis |
| title_full | Research on professional talent training technology based on multimedia remote image analysis |
| title_fullStr | Research on professional talent training technology based on multimedia remote image analysis |
| title_full_unstemmed | Research on professional talent training technology based on multimedia remote image analysis |
| title_short | Research on professional talent training technology based on multimedia remote image analysis |
| title_sort | research on professional talent training technology based on multimedia remote image analysis |
| topic | Multimedia Distance learning Professional talent Training Image |
| url | http://link.springer.com/article/10.1186/s13640-019-0437-4 |
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