基于边缘计算的多摄像头视频协同分析方法

doi:10.11959/j.issn.1000-436x.2023150

Abstract

Abstract:

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.

Key words: edge computing, machine learning, video collaborative analysis, region of interest annotation, association between cameras

CLC Number:

TN919.85

Zhibo QI, Lei DU, Ru HUO, Fan YANG, Tao HUANG. Multi-camera video collaborative analysis method based on edge computing[J]. Journal on Communications, 2023, 44(8): 14-26.

Figures/Tables 8

参数	含义
N	摄像头集合
Ms	主边缘服务器
M	直连边缘服务器集合
T	时间段，组成单元为时隙
$r_{n_{z}}$	摄像头n_z 的传输速率
$r_{m_{z}}$	直连边缘服务器m_z的传输速率
$W_{t}$	摄像头n_z 在t时隙的上行带宽
$P_{n_{z}}$	摄像头n_z 的传输功率
$G_{n_{z}}$	摄像头n_z 到直连边缘服务器的信道增益
$σ^{2}$	背景噪声方差
$D_{n_{z}}^{tran}$	摄像头n_z 到直连边缘服务器的传输时延
$D_{n_{z}}^{tran}$	直连边缘服务器n_z 到主边缘服务器或云服务器的传输时延
$D_{n_{z}}^{com}$	计算时延

时隙	检测到的目标物体	区域块集合
t	$L_{t} = {l_{1}, l_{2}, l_{3}, l_{4}, l_{5}, l_{6}, l_{7}, l_{8}, l_{9}, l_{10}}$	${RS}_{t}^{1} = {{R_{1, 9}, R_{1, 10}, R_{1, 13}, R_{1, 14}}, {R_{2, 1}, R_{2, 2}, R_{2, 5}, R_{2, 6}}}$
		${RS}_{t}^{2} = {{R_{1, 5}, R_{1, 6}, R_{1, 9}, R_{1, 10}, R_{1, 14}}, {R_{2, 2}, R_{2, 6}}}$
		${RS}_{t}^{3} = {{R_{1, 2}, R_{1, 6}}, {R_{2, 3}, R_{2, 4}, R_{2, 7}, R_{2, 8}}, {R_{4, 6}, R_{4, 10}, R_{4, 14}}}$
		${RS}_{t}^{4} = {{R_{1, 2}, R_{1, 6}}, {R_{2, 5}, R_{2, 7}}, {R_{4, 7}, R_{4, 11}}}$
		${RS}_{t}^{5} = {{R_{1, 2}, R_{1, 6}}, {R_{2, 5}, R_{2, 7}}}$
		${RS}_{t}^{6} = {{R_{2, 2}, R_{2, 6}}}$
		${RS}_{t}^{7} = {{R_{3, 5}, R_{3, 6}, R_{3, 9}, R_{3, 10}}, {R_{4, 7}, R_{4, 8}, R_{4, 11}, R_{4, 12}}}$
		${RS}_{t}^{8} = {{R_{3, 5}, R_{3, 9}}, {R_{4, 8}, R_{4, 12}}}$
		${RS}_{t}^{9} = {{R_{3, 7}, R_{3, 11}, R_{3, 15}}}$
		${RS}_{t}^{10} = {{R_{4, 2}, R_{4, 6}}}$

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