Research on multi-stream variable resolution compression and transmission technology based on scene elements in Internet of things environment
In response to the demand of wide coverage and massive access,low bandwidth and low power consumption is an important research direction to solve this problem.In smart cities,security monitoring and other application areas,video surveillance based on the region of interest of the face are particular...
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| Format: | Article |
| Language: | zho |
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China InfoCom Media Group
2018-12-01
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| Series: | 物联网学报 |
| Subjects: | |
| Online Access: | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2018.00075/ |
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| _version_ | 1841531232941244416 |
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| author | Shangwu XIAO Ruimin HU Yu CHEN Jing XIAO |
| author_facet | Shangwu XIAO Ruimin HU Yu CHEN Jing XIAO |
| author_sort | Shangwu XIAO |
| collection | DOAJ |
| description | In response to the demand of wide coverage and massive access,low bandwidth and low power consumption is an important research direction to solve this problem.In smart cities,security monitoring and other application areas,video surveillance based on the region of interest of the face are particularly important.It is a feasible direction to realize the extraction of scene elements,transmission of key information with very low bandwidth and the application of video technology in the Internet of things environment through the strategy of multi-stream differential coding.By designing a face-oriented variable resolution hybrid coding algorithm,the bandwidth could be saved and the power consumption could be reduced greatly,the access requirements of narrowband Internet of things could be met.Through the face detection algorithm based on the deep learning Caffe framework,the face region of interest was acquired in key frames,and the face image was encoded with high resolution.By designing the code rate adaptive allocation algorithm,the bandwidth was utilized rationally,and the encoded face information and the full background content were distinguished.The encoded mixed code stream information was transmitted through the narrowband; the key frame-based face enhancement decoding algorithm was adopted at the receiving end to obtain a partial HD high-definition monitoring picture.Experiments show that when the video encoded by the proposed method is transmitted in a narrow band whose transmission rate is 120~160 kbit/s,the face image can maintain the same definition as the original HD monitoring acquisition end,which has strong practicability. |
| format | Article |
| id | doaj-art-34b51b732a6b40a38d27d00854f9975a |
| institution | Kabale University |
| issn | 2096-3750 |
| language | zho |
| publishDate | 2018-12-01 |
| publisher | China InfoCom Media Group |
| record_format | Article |
| series | 物联网学报 |
| spelling | doaj-art-34b51b732a6b40a38d27d00854f9975a2025-01-15T02:52:11ZzhoChina InfoCom Media Group物联网学报2096-37502018-12-012313959643730Research on multi-stream variable resolution compression and transmission technology based on scene elements in Internet of things environmentShangwu XIAORuimin HUYu CHENJing XIAOIn response to the demand of wide coverage and massive access,low bandwidth and low power consumption is an important research direction to solve this problem.In smart cities,security monitoring and other application areas,video surveillance based on the region of interest of the face are particularly important.It is a feasible direction to realize the extraction of scene elements,transmission of key information with very low bandwidth and the application of video technology in the Internet of things environment through the strategy of multi-stream differential coding.By designing a face-oriented variable resolution hybrid coding algorithm,the bandwidth could be saved and the power consumption could be reduced greatly,the access requirements of narrowband Internet of things could be met.Through the face detection algorithm based on the deep learning Caffe framework,the face region of interest was acquired in key frames,and the face image was encoded with high resolution.By designing the code rate adaptive allocation algorithm,the bandwidth was utilized rationally,and the encoded face information and the full background content were distinguished.The encoded mixed code stream information was transmitted through the narrowband; the key frame-based face enhancement decoding algorithm was adopted at the receiving end to obtain a partial HD high-definition monitoring picture.Experiments show that when the video encoded by the proposed method is transmitted in a narrow band whose transmission rate is 120~160 kbit/s,the face image can maintain the same definition as the original HD monitoring acquisition end,which has strong practicability.http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2018.00075/NB-IoTsurveillance videovariable resolutionvideo codingface detection |
| spellingShingle | Shangwu XIAO Ruimin HU Yu CHEN Jing XIAO Research on multi-stream variable resolution compression and transmission technology based on scene elements in Internet of things environment 物联网学报 NB-IoT surveillance video variable resolution video coding face detection |
| title | Research on multi-stream variable resolution compression and transmission technology based on scene elements in Internet of things environment |
| title_full | Research on multi-stream variable resolution compression and transmission technology based on scene elements in Internet of things environment |
| title_fullStr | Research on multi-stream variable resolution compression and transmission technology based on scene elements in Internet of things environment |
| title_full_unstemmed | Research on multi-stream variable resolution compression and transmission technology based on scene elements in Internet of things environment |
| title_short | Research on multi-stream variable resolution compression and transmission technology based on scene elements in Internet of things environment |
| title_sort | research on multi stream variable resolution compression and transmission technology based on scene elements in internet of things environment |
| topic | NB-IoT surveillance video variable resolution video coding face detection |
| url | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2018.00075/ |
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