Research on Human Motion Recognition Based on Data Redundancy Technology
Aiming at the problems of low recognition rate and slow recognition speed of traditional body action recognition methods, a human action recognition method based on data deduplication technology is proposed. Firstly, the data redundancy technology and perceptual hashing technology are combined to fo...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5542892 |
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| _version_ | 1832547675119026176 |
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| author | Hong-Lan Yang Meng-Zhe Huang Zheng-Qun Cai |
| author_facet | Hong-Lan Yang Meng-Zhe Huang Zheng-Qun Cai |
| author_sort | Hong-Lan Yang |
| collection | DOAJ |
| description | Aiming at the problems of low recognition rate and slow recognition speed of traditional body action recognition methods, a human action recognition method based on data deduplication technology is proposed. Firstly, the data redundancy technology and perceptual hashing technology are combined to form an index, and the image is filtered from the structure, color, and texture features of human action image to achieve image redundancy processing. Then, the depth feature of processed image is extracted by depth motion map; finally, feature recognition is carried out by convolution neural network so as to achieve the purpose of human action recognition. The simulation results show that the proposed method can obtain the optimal recognition results and has strong robustness. At the same time, it also fully proves the importance of human motion recognition. |
| format | Article |
| id | doaj-art-e73f5fbd60c148c4aa36b2e4f9812540 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-e73f5fbd60c148c4aa36b2e4f98125402025-02-03T06:43:55ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55428925542892Research on Human Motion Recognition Based on Data Redundancy TechnologyHong-Lan Yang0Meng-Zhe Huang1Zheng-Qun Cai2School of Computer Engineering, Anhui Wenda University of Information Engineering, Hefei 231201, ChinaSchool of Film and TV Media, Anhui Wenda University of Information Engineering, Hefei 231201, ChinaSchool of Foreign Studies, Anhui Jianzhu University, Hefei 231201, ChinaAiming at the problems of low recognition rate and slow recognition speed of traditional body action recognition methods, a human action recognition method based on data deduplication technology is proposed. Firstly, the data redundancy technology and perceptual hashing technology are combined to form an index, and the image is filtered from the structure, color, and texture features of human action image to achieve image redundancy processing. Then, the depth feature of processed image is extracted by depth motion map; finally, feature recognition is carried out by convolution neural network so as to achieve the purpose of human action recognition. The simulation results show that the proposed method can obtain the optimal recognition results and has strong robustness. At the same time, it also fully proves the importance of human motion recognition.http://dx.doi.org/10.1155/2021/5542892 |
| spellingShingle | Hong-Lan Yang Meng-Zhe Huang Zheng-Qun Cai Research on Human Motion Recognition Based on Data Redundancy Technology Complexity |
| title | Research on Human Motion Recognition Based on Data Redundancy Technology |
| title_full | Research on Human Motion Recognition Based on Data Redundancy Technology |
| title_fullStr | Research on Human Motion Recognition Based on Data Redundancy Technology |
| title_full_unstemmed | Research on Human Motion Recognition Based on Data Redundancy Technology |
| title_short | Research on Human Motion Recognition Based on Data Redundancy Technology |
| title_sort | research on human motion recognition based on data redundancy technology |
| url | http://dx.doi.org/10.1155/2021/5542892 |
| work_keys_str_mv | AT honglanyang researchonhumanmotionrecognitionbasedondataredundancytechnology AT mengzhehuang researchonhumanmotionrecognitionbasedondataredundancytechnology AT zhengquncai researchonhumanmotionrecognitionbasedondataredundancytechnology |