Realtime flicker removal for fast video streaming and detection of moving objects

被引:0
|
作者
Jarosław Nowisz
Michał Kopania
Artur Przelaskowski
机构
[1] Warsaw University of Technology,Faculty of Mathematics and Information Science
来源
关键词
Flickering removal; Video processing; Movement detection; Intensity flicker; Object tracking;
D O I
暂无
中图分类号
学科分类号
摘要
High-speed cameras are used in computer vision systems to track balls, shuttlecocks, or players in many different sports. Collected information is used for statistics, as coaches’ and players’ aids to improve technique and tactics or as referees’ aids to verify their decisions or to enrich television broadcasts. Sports arenas in which games are played are often equipped with lights generating flickering effects in captured movies. A fast and yet effective enough algorithm is necessary to remove flickering so movement detection and object tracking algorithms could be used. In this paper, we propose a fast flicker removal algorithm working as an online filter on frame streams at speeds exceeding 200 frames per second. Most of the solutions found in literature concentrate on effectiveness and accuracy and not on the speed of operation. In contrast, our original solution is designed with speed in mind with sufficient accuracy to be used before calculating differential frames to detect movement in streams. Our algorithm is adaptive and works when lighting conditions are changing (new light sources) and performs well with various light sources that are causing flickering. The results of the experiments carried out show the high effectiveness of the method implemented on CPU and GPU, allowing effective tracking of objects of interest in preliminary applications of a commercially offered instant review system for badminton.
引用
收藏
页码:14941 / 14960
页数:19
相关论文
共 50 条
  • [31] SPEM online rate control for realtime streaming video
    Nguyen, AG
    Hwang, JN
    INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY: CODING AND COMPUTING, PROCEEDINGS, 2002, : 65 - 70
  • [32] Efficient Moving Objects Detection by Lidar for Rain Removal
    Wang, Yao
    Fu, Fangfa
    Shi, Jinjin
    Xu, Weizhe
    Wang, Jinxiang
    INTELLIGENT COMPUTING METHODOLOGIES, ICIC 2016, PT III, 2016, 9773 : 697 - 706
  • [33] Fast Approximated SIFT Applied in Moving Objects Detection
    Tang, Wei
    Wang, Zhaoshun
    PROCEEDINGS OF THE 2008 CHINESE CONFERENCE ON PATTERN RECOGNITION (CCPR 2008), 2008, : 205 - 208
  • [34] A Novel Algorithm for Fast Speckled Beacon Flicker Objects Detection in Complicated Environment
    Liu, Haiying
    Mu, Xingyu
    Deng, Lixia
    Zhao, Yang
    2021 IEEE International Conference on Artificial Intelligence and Computer Applications, ICAICA 2021, 2021, : 1057 - 1060
  • [35] Detection and Parameters Estimation of Moving Objects via Video Surveillance
    Garvanov, Ivan
    Ivanov, Vladimir
    PROCEEDINGS OF 2019 3RD INTERNATIONAL CONFERENCE ON AUTOMATION, CONTROL AND ROBOTS (ICACR 2019), 2018, : 102 - 106
  • [36] Moving Objects Detection in Video Sequences Captured by a PTZ Camera
    Lin, Li
    Wang, Bin
    Wu, Fen
    Cao, Fengyin
    IMAGE AND GRAPHICS (ICIG 2017), PT III, 2017, 10668 : 287 - 298
  • [37] Robust Detection and Tracking of Moving Objects in Traffic Video Surveillance
    Antic, Borislav
    Castaneda, Jorge Oswaldo Nino
    Culibrk, Dubravko
    Pizurica, Aleksandra
    Crnojevic, Vladimir
    Philips, Wilfried
    ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, PROCEEDINGS, 2009, 5807 : 494 - +
  • [38] Unsupervised detection and tracking of moving objects for video surveillance applications
    Elafi, Issam
    Jedra, Mohamed
    Zahid, Noureddine
    PATTERN RECOGNITION LETTERS, 2016, 84 : 70 - 77
  • [39] Real-time detection of moving objects in video sequences
    宋红
    石峰
    JournalofSystemsEngineeringandElectronics, 2005, (03) : 687 - 691
  • [40] An adaptive graph cut algorithm for video moving objects detection
    Chunsheng Guo
    Dan Liu
    YunFei Guo
    Yao Sun
    Multimedia Tools and Applications, 2014, 72 : 2633 - 2652