Multi-camera video collaborative analysis method based on edge computing
In order to reduce the processing volume of multi-camera real-time video data in smart city scenarios, a video collaborative analysis method based on machine learning algorithms at the edge was proposed.Firstly, for the important objects detected by each camera, different key windows were designed t...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2023-08-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023150/ |
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| _version_ | 1841540079192899584 |
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| author | Zhibo QI Lei DU Ru HUO Fan YANG Tao HUANG |
| author_facet | Zhibo QI Lei DU Ru HUO Fan YANG Tao HUANG |
| author_sort | Zhibo QI |
| collection | DOAJ |
| description | In order to reduce the processing volume of multi-camera real-time video data in smart city scenarios, a video collaborative analysis method based on machine learning algorithms at the edge was proposed.Firstly, for the important objects detected by each camera, different key windows were designed to filter the region of interest (RoI) in the video, reduce the video data volume and extract its features.Then, based on the extracted data features, the same objects in the videos from different cameras were annotated, and a strategy for calculating the association degree value between cameras was designed for further reducing the video data volume.Finally, the GC-ReID algorithm based on graph convolutional network (GCN) and re-identification (ReID) was proposed, aiming at achieving the collaborative analysis of multi-camera videos.The experimental results show that proposed method can effectively reduce the system latency and improve the video compression rate while ensuring the high accuracy, compared with the existing video analysis methods. |
| format | Article |
| id | doaj-art-dffd9e4dd1ef4cc19e3d74d1119aa568 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2023-08-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-dffd9e4dd1ef4cc19e3d74d1119aa5682025-01-14T06:22:43ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2023-08-0144142659385637Multi-camera video collaborative analysis method based on edge computingZhibo QILei DURu HUOFan YANGTao HUANGIn order to reduce the processing volume of multi-camera real-time video data in smart city scenarios, a video collaborative analysis method based on machine learning algorithms at the edge was proposed.Firstly, for the important objects detected by each camera, different key windows were designed to filter the region of interest (RoI) in the video, reduce the video data volume and extract its features.Then, based on the extracted data features, the same objects in the videos from different cameras were annotated, and a strategy for calculating the association degree value between cameras was designed for further reducing the video data volume.Finally, the GC-ReID algorithm based on graph convolutional network (GCN) and re-identification (ReID) was proposed, aiming at achieving the collaborative analysis of multi-camera videos.The experimental results show that proposed method can effectively reduce the system latency and improve the video compression rate while ensuring the high accuracy, compared with the existing video analysis methods.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023150/edge computingmachine learningvideo collaborative analysisregion of interest annotationassociation between cameras |
| spellingShingle | Zhibo QI Lei DU Ru HUO Fan YANG Tao HUANG Multi-camera video collaborative analysis method based on edge computing Tongxin xuebao edge computing machine learning video collaborative analysis region of interest annotation association between cameras |
| title | Multi-camera video collaborative analysis method based on edge computing |
| title_full | Multi-camera video collaborative analysis method based on edge computing |
| title_fullStr | Multi-camera video collaborative analysis method based on edge computing |
| title_full_unstemmed | Multi-camera video collaborative analysis method based on edge computing |
| title_short | Multi-camera video collaborative analysis method based on edge computing |
| title_sort | multi camera video collaborative analysis method based on edge computing |
| topic | edge computing machine learning video collaborative analysis region of interest annotation association between cameras |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2023150/ |
| work_keys_str_mv | AT zhiboqi multicameravideocollaborativeanalysismethodbasedonedgecomputing AT leidu multicameravideocollaborativeanalysismethodbasedonedgecomputing AT ruhuo multicameravideocollaborativeanalysismethodbasedonedgecomputing AT fanyang multicameravideocollaborativeanalysismethodbasedonedgecomputing AT taohuang multicameravideocollaborativeanalysismethodbasedonedgecomputing |