Maneuvering target recognition method based on multi-perspective light field reconstruction
It is difficult to reconstruct the complete light field, and the reconstructed light field can only recognize specific fixed targets. These have limited the applications of the light field in practice. To solve the problems above, this article introduces the multi-perspective distributed information...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-08-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147719870657 |
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| _version_ | 1849703198971920384 |
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| author | Lei Cai Peien Luo Guangfu Zhou Zhenxue Chen |
| author_facet | Lei Cai Peien Luo Guangfu Zhou Zhenxue Chen |
| author_sort | Lei Cai |
| collection | DOAJ |
| description | It is difficult to reconstruct the complete light field, and the reconstructed light field can only recognize specific fixed targets. These have limited the applications of the light field in practice. To solve the problems above, this article introduces the multi-perspective distributed information fusion into light field reconstruction to monitor and recognize the maneuvering targets. First, the light field is represented as sub-light fields at different perspectives (i.e. the Multi-sensor distributed network), and sparse representation and reconstruction are then performed. Second, we establish the multi-perspective distributed information fusion under the condition of regional full-coverage constraints. Finally, the light field data from multiple perspectives are fused and the states of the maneuvering targets are estimated. Experimental results show that the light field reconstruction time of the proposed method is less than 583 s, and the reconstruction accuracy exceeds 92.447% compared with the existing spatially variable bidirectional reflectance distribution function, micro-lens array, and others. In the aspect of maneuvering target recognition, the recognition time of the algorithm in this article is no more than 3.5 s. The recognition accuracy of the algorithm in this article is up to 86.739%. Moreover, the more viewing angles used, the higher the accuracy. |
| format | Article |
| id | doaj-art-08b4d7799ce74d12a03e551fb67cc4fd |
| institution | DOAJ |
| issn | 1550-1477 |
| language | English |
| publishDate | 2019-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-08b4d7799ce74d12a03e551fb67cc4fd2025-08-20T03:17:23ZengWileyInternational Journal of Distributed Sensor Networks1550-14772019-08-011510.1177/1550147719870657Maneuvering target recognition method based on multi-perspective light field reconstructionLei Cai0Peien Luo1Guangfu Zhou2Zhenxue Chen3School of Information and Engineering, Henan Institute of Science and Technology, Xinxiang, P.R. ChinaSchool of Information and Engineering, Henan Institute of Science and Technology, Xinxiang, P.R. ChinaSchool of Information and Engineering, Henan Institute of Science and Technology, Xinxiang, P.R. ChinaSchool of Control Science and Engineering, Shandong University, Jinan, P.R. ChinaIt is difficult to reconstruct the complete light field, and the reconstructed light field can only recognize specific fixed targets. These have limited the applications of the light field in practice. To solve the problems above, this article introduces the multi-perspective distributed information fusion into light field reconstruction to monitor and recognize the maneuvering targets. First, the light field is represented as sub-light fields at different perspectives (i.e. the Multi-sensor distributed network), and sparse representation and reconstruction are then performed. Second, we establish the multi-perspective distributed information fusion under the condition of regional full-coverage constraints. Finally, the light field data from multiple perspectives are fused and the states of the maneuvering targets are estimated. Experimental results show that the light field reconstruction time of the proposed method is less than 583 s, and the reconstruction accuracy exceeds 92.447% compared with the existing spatially variable bidirectional reflectance distribution function, micro-lens array, and others. In the aspect of maneuvering target recognition, the recognition time of the algorithm in this article is no more than 3.5 s. The recognition accuracy of the algorithm in this article is up to 86.739%. Moreover, the more viewing angles used, the higher the accuracy.https://doi.org/10.1177/1550147719870657 |
| spellingShingle | Lei Cai Peien Luo Guangfu Zhou Zhenxue Chen Maneuvering target recognition method based on multi-perspective light field reconstruction International Journal of Distributed Sensor Networks |
| title | Maneuvering target recognition method based on multi-perspective light field reconstruction |
| title_full | Maneuvering target recognition method based on multi-perspective light field reconstruction |
| title_fullStr | Maneuvering target recognition method based on multi-perspective light field reconstruction |
| title_full_unstemmed | Maneuvering target recognition method based on multi-perspective light field reconstruction |
| title_short | Maneuvering target recognition method based on multi-perspective light field reconstruction |
| title_sort | maneuvering target recognition method based on multi perspective light field reconstruction |
| url | https://doi.org/10.1177/1550147719870657 |
| work_keys_str_mv | AT leicai maneuveringtargetrecognitionmethodbasedonmultiperspectivelightfieldreconstruction AT peienluo maneuveringtargetrecognitionmethodbasedonmultiperspectivelightfieldreconstruction AT guangfuzhou maneuveringtargetrecognitionmethodbasedonmultiperspectivelightfieldreconstruction AT zhenxuechen maneuveringtargetrecognitionmethodbasedonmultiperspectivelightfieldreconstruction |