UNIVERSAL MULTI MODE BACKGROUND SUBTRACTION

International Journal of Computer Science (IJCS Journal) Published by SK Research Group of Companies (SKRGC) Scholarly Peer Reviewed Research Journals

Format: Volume 6, Issue 1, No 01, 2018

Copyright: All Rights Reserved ©2018

Year of Publication: 2018

Author: Mrs.S. Anitha, Ms.Sugashini Sappani, Ms.B.Prema

Reference:IJCS-329

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Abstract

In this paper, we present a complete change detection system named multimode background subtraction. The universal nature of system allows it to robustly handle multitude of challenges associated with video change detection, such as illumination changes, dynamic background, camera jitter, and moving camera. The system comprises multiple innovative mechanisms in background modeling, model update, pixel classification, and the use of multiple color spaces. The system first creates multiple background models of the scene followed by an initial foreground/background probability estimation for each pixel. Next, the image pixels are merged together to form megapixels, which are used to spatially denoise the initial probability estimates to generate binary masks for both RGB and YCbCr color spaces. The masks generated after processing these input images are then combined to separate foreground pixels from the background. Comprehensive evaluation of the proposed approach on publicly available test sequences from the CDnet and the ESI data sets shows superiority in the performance of our system over other state-of-the-art algorithms.

References

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[2] Y. Wang, P.-M. Jodoin, F. Porikli, J. Konrad, Y. Benezeth, and P. Ishwar, “CDnet 2014: An expanded change detection benchmark dataset,” in Proc. Comput. Vis. Pattern Recognit. Workshops (CVPRW), 2014, pp. 387–394.

[3] Changedetection Dataset, accessed on Dec. 15, 2016. [Online]. Available: https://www.changedetection.net

[4] H. Sajid and S.-C. S. Cheung, “Background subtraction under sudden illumination change,” in Proc. IEEE Multimedia Signal Process. (MMSP), Sep. 2014, pp. 1–6.

[5] H. Sajid and S.-C. S. Cheung, “Background subtraction for static moving camera,” in Proc. Int. Conf. Image Process., Sep. 2015, pp. 4530–4534.


Keywords

Computer vision, change detection, background model bank, background subtraction, color spaces, binary classifiers, foreground segmentation, pixel classification.

This work is licensed under a Creative Commons Attribution 3.0 Unported License.   

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