基于SEI的煤矿智能监控视频传输方法

陈佳; 王琪; 王鹏

doi:10.13272/j.issn.1671-251x.2023100025

基于SEI的煤矿智能监控视频传输方法

doi: 10.13272/j.issn.1671-251x.2023100025

陈佳^{1, 2,},
王琪^{1, 2},
王鹏^{1, 2}

1.
中煤科工集团常州研究院有限公司，江苏常州　213015
2.
天地（常州）自动化股份有限公司，江苏常州　210315

基金项目: 中煤科工集团常州研究院科研项目（2024GY0003）。

详细信息

作者简介:
陈佳（1994—），男，安徽铜陵人，硕士，主要从事煤矿智能视频平台开发工作，E-mail：cj068@mail.ustc.edu.cn

中图分类号: TD76
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- PDF下载量: 14
- 被引次数: 0
出版历程
- 收稿日期: 2023-10-10
- 修回日期: 2024-05-18
- 网络出版日期: 2024-06-13

SEI based intelligent monitoring video transmission method for coal mines

CHEN Jia^{1, 2
,},
WANG Qi^{1, 2},
WANG Peng^{1, 2}

1.
CCTEG Changzhou Research Institute, Changzhou 213015, China
2.
Tiandi (Changzhou) Automation Co., Ltd., Changzhou 210315 , China

摘要

摘要: 目前煤矿视频监控数据传输存在高延迟问题，而视频传输延迟的主要成因是编码延迟。针对该问题，提出了一种无视频编码的基于媒体补充增强信息（SEI）的煤矿智能监控视频传输方法。该方法在解复用视频流得到视频压缩帧后缓存一份副本，解码视频压缩帧得到视频解码帧，通过SEI存储视频解码帧中AI模型分析结果，根据时间戳对应关系将自定义SEI写入该视频解码帧对应视频压缩帧副本的网络提取层单元，并复用视频压缩帧副本，实现煤矿智能监控视频实时传输。在24核CPU上对该方法进行实验测试，结果表明：对于1 280×720分辨率的视频，采用该方法处理视频时CPU整体使用率由采用传统方法时的24.7%～36.6%降至20.3%～23.9%，端到端延迟由1 946 ms降至345 ms；对于1 920×1 080分辨率的视频，采用该方法处理视频时CPU整体使用率由采用传统方法时的29.2%～41.8%降至18.5%～26.3%，端到端延迟由6 204 ms降至479 ms。该方法通过规避视频编码环节，降低了煤矿智能监控视频传输延迟，且节省了视频编码所需的CPU或GPU资源，降低了智能视频监控系统硬件成本。
- 煤矿智能视频监控 /
- 监控视频传输 /
- 视频AI分析 /
- 无视频编码 /
- 媒体补充增强信息 /
- 端到端延迟
Abstract: Currently, there is a high latency problem in the transmission of video surveillance data in coal mines, and the main cause of video transmission delay is encoding delay. In order to solve the above problems, a intelligent monitoring video transmission method for coal mines based on media supplemental enhancement information(SEI) without video encoding is proposed. This method caches a copy of the compressed video frame obtained by demultiplexing the video stream, and decodes the compressed video frame to obtain the decoded video frame. The method stores the AI model analysis results in the decoded video frame through SEI, writes the custom SEI into the network extraction layer unit corresponding to the compressed video frame copy of the decoded video frame based on the timestamp correspondence. The method multiplexes the compressed video frame copy to achieve real-time transmission of coal mine intelligent monitoring videos. Experimental testing of this method is conducted on a 24 core CPU. The results show that for videos with a resolution of 1280×720, the overall CPU utilization rate for video processing using this method decreases from 24.7% to 36.3% when using traditional methods to 20.3% to 23.9%. The end-to-end delay decreases from 1946 ms to 345 ms. For videos with a resolution of 1920×1080, the overall CPU utilization rate for video processing using this method decreases from 29.2% to 41.8% using traditional methods to 18.5% to 26.3%. The end-to-end latency decreases from 6204 ms to 479 ms. This method reduces the transmission delay of coal mine intelligent monitoring videos by avoiding the video encoding process, saves CPU or GPU resources required for video encoding, and reduces the hardware cost of the intelligent video monitoring system.
- intelligent video surveillance for coal mines /
- monitoring video transmission /
- AI analysis of video /
- no video encoding /
- media supplement and enhance information /
- end to end latency

HTML全文

图 1 基于SEI的煤矿智能监控视频传输方法

Figure 1. Intelligent monitoring video transmission method for coal mine based on supplemental enhancement information (SEI)

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图 2 解码流程示例

Figure 2. Example of decoding process

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图 3 自定义SEI结构

Figure 3. Structure of customized SEI

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图 4 YOLOv5模型检测结果

Figure 4. YOLOv5 model detection results

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图 5 视频处理过程中CPU使用率

Figure 5. CPU usage in video processing

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图 6 端到端延迟测试方法

Figure 6. End-to-end latency test method

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表 1 编码器参数设置

Table 1. Encoder parameters of H.264 encoder

参数值

preset medium
framerate 30
gop_size 30
open-gop false
no-scenecut true
forced-idr true
x264-params keyint=30:keyint_min=30:rc-lookahead=10

下载: 导出CSV

表 2 视频传输端到端延迟测试结果

Table 2. Test results of end-to-end latency of video transmission ms

视频端到端延迟

传统方法本文方法

1 1 946 345

2 6 204 479

下载: 导出CSV

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