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A Feedback-Based Robust Video Stabilization Method for Traffic Videos
Ling, Qiang1; Deng, Sibin1; Li, Feng1; Huang, Qinghua2,3,4; Li, Xuelong5
Department光学影像学习与分析中心
2018-03-01
Source PublicationIEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
ISSN1051-8215
Volume28Issue:3Pages:561-572
Contribution Rank5
Abstract

Traffic videos are often recorded by vehicle-mounted cameras. Compared with videos recorded by handheld cameras, traffic videos suffer from more challenges, such as higher frequency and more violent jitters, dynamic scenes, large moving objects, and parallax, which can result in significant visual quality degradation. To address these challenges for traffic videos, we propose a special stabilization method. The key aspect of our method is a feedback strategy that divides the extracted feature trajectories into background trajectories and foreground trajectories by feeding back the previous trajectory classification results. The method can perform robustly, even in the case of large moving objects and parallax. Furthermore, our method maintains the number of available background trajectories within a reasonable range via two refinement strategies. One strategy attempts to reliably recover background trajectories from misjudged foreground trajectories when there are an insufficient number of background trajectories. The other strategy can adaptively adjust the number of feature points in each frame to efficiently avoid too many or too few background trajectories. With the obtained background trajectories, a homography matrix between each frame and its stabilized view is computed and implemented to warp the frame image to produce smooth videos. Experimental results confirm that our method is both effective in stabilizing traffic videos and quite robust against large moving objects and parallax.

 

KeywordFeature Trajectory Feedback Traffic Videos Video Stabilization
DOI10.1109/TCSVT.2016.2618934
Indexed BySCI ; EI
Language英语
WOS IDWOS:000426693100001
EI Accession Number20181004882979
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/30750
Collection光学影像学习与分析中心
Affiliation1.Univ Sci & Technol China, Dept Automat, Hefei 230027, Anhui, Peoples R China;
2.Shenzhen Univ, Coll Informat Engn, Shenzhen 518060, Peoples R China;
3.South China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510641, Guangdong, Peoples R China;
4.Guangzhou Key Lab Body Data Sci, Guangzhou 510641, Guangdong, Peoples R China;
5.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Ctr OPT IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian 710119, Shaanxi, Peoples R China
Recommended Citation
GB/T 7714
Ling, Qiang,Deng, Sibin,Li, Feng,et al. A Feedback-Based Robust Video Stabilization Method for Traffic Videos[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2018,28(3):561-572.
APA Ling, Qiang,Deng, Sibin,Li, Feng,Huang, Qinghua,&Li, Xuelong.(2018).A Feedback-Based Robust Video Stabilization Method for Traffic Videos.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,28(3),561-572.
MLA Ling, Qiang,et al."A Feedback-Based Robust Video Stabilization Method for Traffic Videos".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 28.3(2018):561-572.
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