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NIC: a robust background extraction algorithm for foreground detection in dynamic scenes


Huynh-The, T and Banos, O and Lee, S and Kang, BH and Kim, ES and Le-Tien, T, NIC: a robust background extraction algorithm for foreground detection in dynamic scenes, IEEE Transactions on Circuits and Systems for Video Technology, 27, (7) pp. 1478-1490. ISSN 1051-8215 (2017) [Refereed Article]

Copyright Statement

Copyright 2016 IEEE

DOI: doi:10.1109/TCSVT.2016.2543118


This paper presents a robust foreground detection method capable of adapting to different motion speeds in scenes. A key contribution of this work is the background estimation using a proposed novel algorithm, Neighbor-based Intensity Correction (NIC), that identifies and modifies the motion pixels from the difference of the background and the current frame. Concretely, the first frame is considered as an initial background that is updated with the pixel intensity from each new frame based on the examination of neighborhood pixels. These pixels are formed into windows, generated from the background and the current frame, to identify whether a pixel belongs to the background or the current frame. The intensity modification procedure is based on the comparison of the standard deviation values calculated from two pixel windows. The robustness of the current background is further measured using pixel steadiness as an additional condition for the updating process. Finally, the foreground is detected by the background subtraction scheme with an optimal threshold calculated by the Otsu method. This method is benchmarked on several well-known datasets in the object detection and tracking domain, such as CAVIAR 2004, CAVIAR 2007, PETS 2009, PETS 2014, and CDNET 2014. We also compare the accuracy of the proposed method with other state-of-the-art methods via standard quantitative metrics under different parameter configurations. In the experiments, NIC approach outperforms several advanced methods on depressing the detected foreground confusions due to light artifact, illumination change, and camera jitter in dynamic scenes.

Item Details

Item Type:Refereed Article
Keywords:background subtraction, foreground detection, neighbor-based intensity correction, adaptive Otsu thresholding
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Mobile computing
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Kang, BH (Professor Byeong Kang)
ID Code:115279
Year Published:2017 (online first 2016)
Web of Science® Times Cited:25
Deposited By:Engineering
Deposited On:2017-03-14
Last Modified:2017-11-15

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