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Real-Time Moving Targets Detection in Dynamic Scenes

Fan Li1, Yang Yang

The Ministry of Education Key Laboratory for Intelligent Networks and Network Security, School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, P.R. China, Email: lifan@mail.xjtu.edu.cn

Computer Modeling in Engineering & Sciences 2015, 107(2), 103-124. https://doi.org/10.3970/cmes.2015.107.103

Abstract

The shift of the camera leads to unsteadiness of backgrounds in video sequences. The motion of camera will results in mixture of backgrounds and foregrounds motion. So it is a challenge for targets detection in dynamic scenes. A realtime moving target detection algorithm with low complexity in dynamic scenes is proposed in this paper. Sub-block based image registration is applied to remove the global motion of the video frame. Considering the blocks in one frame have different motion vectors, the global motion of each block is separately estimated. Then, a neighbor-based background modeling is applied to extract the moving objects. Moreover, combination of image registration and neighbor-based background modeling can precisely divided foregrounds from backgrounds. At last, a method, based on feature point motions, is adopted to track the foregrounds in time. The experimental results demonstrate that our method can process videos in real-time, without the effect of time delay. What is more, comparative results by quantitative evaluations manifest that the proposed approach can achieve the best classification accuracy.

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Cite This Article

APA Style
Li, F., Yang, Y. (2015). Real-time moving targets detection in dynamic scenes. Computer Modeling in Engineering & Sciences, 107(2), 103-124. https://doi.org/10.3970/cmes.2015.107.103
Vancouver Style
Li F, Yang Y. Real-time moving targets detection in dynamic scenes. Comput Model Eng Sci. 2015;107(2):103-124 https://doi.org/10.3970/cmes.2015.107.103
IEEE Style
F. Li and Y. Yang, “Real-Time Moving Targets Detection in Dynamic Scenes,” Comput. Model. Eng. Sci., vol. 107, no. 2, pp. 103-124, 2015. https://doi.org/10.3970/cmes.2015.107.103



cc Copyright © 2015 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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