[1]刘 存,杨曦晨,陈天海,等.视频质量波动影响下的视频异常检测算法有效性分析[J].常州大学学报(自然科学版),2024,36(03):45-58.[doi:10.3969/j.issn.2095-0411.2024.03.006]
　LIU Cun,YANG Xichen,CHEN Tianhai,et al.Effectivity analysis of video anomaly detection algorithm with video quality fluctuation[J].Journal of Changzhou University(Natural Science Edition),2024,36(03):45-58.[doi:10.3969/j.issn.2095-0411.2024.03.006]
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视频质量波动影响下的视频异常检测算法有效性分析()
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常州大学学报(自然科学版)[ISSN:2095-0411/CN:32-1822/N]

卷:
第36卷
期数:
2024年03期
页码:
45-58
栏目:
计算机与信息工程
出版日期:
2024-05-28

文章信息/Info

Title:
Effectivity analysis of video anomaly detection algorithm with video quality fluctuation
文章编号:
2095-0411(2024)03-0045-14
作者:
刘 存;  杨曦晨;  陈天海;  吉根林
南京师范大学 计算机与电子信息学院, 江苏 南京 210023
Author(s):
LIU Cun;  YANG Xichen;  CHEN Tianhai;  JI Genlin
School of Computer and Electronic Information, Nanjing Normal University, Nanjing 210023, China
关键词:
异常检测;  质量波动;  仿真;  失真;  有效性
Keywords:
anomaly detection;  quality fluctuation;  simulation;  distortion;  effectiveness
分类号:
TP 391
DOI:
10.3969/j.issn.2095-0411.2024.03.006
文献标志码:
A
摘要:
大部分异常检测算法并没有考虑实际场景中视频质量波动对算法性能的影响。文章首先选用视频异常检测领域的公开数据集,并采用仿真方式在其中加入监控视频中的常见失真,构建出面向异常检测的失真数据集。然后系统地分析了视频质量波动对4个经典的视频异常检测算法性能的影响。实验结果表明,监控数据质量下降会对视频异常检测算法的有效性产生负面效果,并且不同失真类型、不同失真程度对算法的影响存在差异,其中高斯噪声失真和过亮失真对算法的影响较大。
Abstract:
As most anomaly detection methods generally ignore the impact of video quality fluctuations in actual scenarios on their performance. Firstly, public datasets from the field of video anomaly detection were selected, and a distortion dataset for anomaly detection by artificially introducing common distortions found in surveillance videos through simulation methods was constructed. This paper systematically analyzes the impact of video quality fluctuations on the performance of four classic video anomaly detection algorithms. And the experimental results show that the degradation of surveillance data quality have a negative effect on the effectiveness of the video anomaly detection algorithm. Moreover, the impact of different distortion types and different degrees of distortion on the algorithm is different, as well as, Gaussian noise distortion and over brightness distortion have a greater impact on the algorithm.

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备注/Memo

备注/Memo:
收稿日期: 2024-01-26。
基金项目: 国家自然科学基金资助项目(41971343); 国家自然科学基金青年基金资助项目(62101268)。
作者简介: 刘存(1999—), 女, 山东济宁人, 硕士生。通信联系人: 吉根林(1964—), E-mail: glji@njnu.edu.cn
更新日期/Last Update: 1900-01-01