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Background Subtraction Algorithm Based on Combination of Grabcut and Improved ViBe

Published: 04 January 2021 Publication History

Abstract

Background subtraction algorithm is essential for video processing. such as target tracing, gesture recognition and gait recognition. ViBe has been widely used because of easy implementation and high efficiency. However, the algorithm would produce a ghost imaging when the speed of the moving target changes. On the other hand, ViBe is challenged to adapt to the change of environment and by misjudge the shadow as the foreground target. Moreover, it is also inability to handle well the interference caused by camera jitter. Aiming to the deficiencies of ViBe, we propose a new algorithm Gc_IViBe, which takes advantages from both Grabcut and Improved ViBe (IViBe). Based on the ability of IViBe to eliminate ghost imaging, the proposed algorithm utilizes mask in HSV space to remove background shadows. A further improvement of the algorithm in handling cavity problem and camera jitter is achieved by combinating IViBe and Grabcut. The experimental results show that Gc_IViBe performs better than ViBe in Pixel-level measure Precision, Structural measures S-measure and E-measure. This paper also discusses the evaluation methods. The evaluation results of Precision and S-measure in some cases are apparently different from the truth. while E-measure performs relatively better consistent, which capable to accurately evaluate the problems raised in this article.

References

[1]
Xu, Y., Ji, H. and Zhang, W. Coarse-to-fine sample-based background subtraction for moving object detection. Optik, 207
[2]
Ling, Z., Li-Min, C., Wei, H. E. and Lei-Min, G. Application of an Improved Frame-difference Method Based on Video in Traffic Flow Measurement. Journal of Chongqing University (2004).
[3]
Zhuo, T., Cheng, Z., Zhang, P., Wong, Y. and Kankanhalli, M. Unsupervised Online Video Object Segmentation With Motion Property Understanding. IEEE Transactions on Image Processing, 29, 1 (2020), 237-249
[4]
Barnich, O. and Van Droogenbroeck, M. ViBE: A powerful random technique to estimate the background in video sequences. City, 2009
[5]
Barnich, O. and Van Droogenbroeck, M. ViBe: A Universal Background Subtraction Algorithm for Video Sequences. Image Processing, IEEE Transactions on, 20, 6 (2011), p.1709-1724.
[6]
Van Droogenbroeck, M. and Paquot, O. Background subtraction: Experiments and improvements for ViBe (2012)
[7]
Lian, X., Zhang, T. and Liu, Z. A Novel Method on Moving-Objects Detection Based on Background Subtraction and Three Frames Differencing. City, 2010
[8]
Rother, C., Kolmogorov, V. and Blake, A. \"GrabCut\". Acm Transactions on Graphics, 23, 3 (2004), 309
[9]
Fan, D. P., Cheng, M. M., Liu, Y., Li, T. and Borji, A. Structure-Measure: A New Way to Evaluate Foreground Maps. City, 2017
[10]
Fan, D. P., Gong, C., Cao, Y., Ren, B., Cheng, M. M. and Borji, A. Enhanced-alignment Measure for Binary Foreground Map Evaluation (2018)

Cited By

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  • (2024)Background Subtraction for Dynamic Scenes Using Gabor Filter Bank and Statistical MomentsAlgorithms10.3390/a1704013317:4(133)Online publication date: 25-Mar-2024
  • (2022)Performance Analysis on Vibe Detection of Moving Object2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)10.1109/ICARCE55724.2022.10046439(1-5)Online publication date: 16-Dec-2022

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cover image ACM Other conferences
CCRIS '20: Proceedings of the 2020 1st International Conference on Control, Robotics and Intelligent System
October 2020
217 pages
ISBN:9781450388054
DOI:10.1145/3437802
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 January 2021

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Author Tags

  1. Background subtraction
  2. Ghost imaging
  3. Shadow
  4. ViBe

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  • Research-article
  • Research
  • Refereed limited

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  • Research on the construction of classroom teaching management information (video-based portraits of student behavior and classroom teaching reform)

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CCRIS 2020

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Cited By

View all
  • (2024)Background Subtraction for Dynamic Scenes Using Gabor Filter Bank and Statistical MomentsAlgorithms10.3390/a1704013317:4(133)Online publication date: 25-Mar-2024
  • (2022)Performance Analysis on Vibe Detection of Moving Object2022 International Conference on Automation, Robotics and Computer Engineering (ICARCE)10.1109/ICARCE55724.2022.10046439(1-5)Online publication date: 16-Dec-2022

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