Challenging situations for background subtraction algorithms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
http://link.springer.com/content/pdf/10.1007/s10489-018-1346-4.pdf
Reference50 articles.
1. Babaee M, Dinh DT, Rigoll G (2018) A deep convolutional neural network for video sequence background subtraction. Pattern Recog 76:635–649. https://doi.org/10.1016/j.patcog.2017.09.040
2. Badura S, Lieskovsky A, Mokrys M (2011) With shadow elimination towards effective foreground extraction. In: 2011 IEEE international symposium on signal processing and information technology (ISSPIT). IEEE, pp 404–408. https://doi.org/10.1109/ISSPIT.2011.6151596
3. Barnich O, Droogenbroeck MV (2011) Vibe: a universal background subtraction algorithm for video sequences. IEEE Trans Image Process 20 (6):1709–1724. https://doi.org/10.1109/TIP.2010.2101613
4. Berjón D, Cuevas C, Morán F, García N (2018) Real-time nonparametric background subtraction with tracking-based foreground update. Pattern Recog 74:156–170. https://doi.org/10.1016/j.patcog.2017.09.009
5. Bianco S, Ciocca G, Schettini R (2017) Combination of video change detection algorithms by genetic programming. IEEE Trans Evol Comput 21(6):914–928. https://doi.org/10.1109/TEVC.2017.2694160
Cited by 17 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Background subtraction for video sequence using deep neural network;Multimedia Tools and Applications;2024-03-13
2. Parallel Computing Using CUDA and MultiThreading in Background Removal Process;2024 3rd International Conference on Digital Transformation and Applications (ICDXA);2024-01-29
3. Automatic generation of difficulty maps for datasets using neural network;Multimedia Tools and Applications;2024-01-23
4. Real-Time Change Detection with Convolutional Density Approximation;Vietnam Journal of Computer Science;2023-10-20
5. $$\mathcal{L}\mathcal{O}^2$$net: Global–Local Semantics Coupled Network for scene-specific video foreground extraction with less supervision;Pattern Analysis and Applications;2023-10-04
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3