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Moving object detection based on optical flow and neural network fusion

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摘要 Purpose-The purpose of this paper is to meet the large demand for the new-generation intelligence monitoring systems that are used to detect targets within a dynamic background.Design/methodology/approach-A dynamic target detection method based on the fusion of optical flow and neural network is proposed.Findings-Simulation results verify the accuracy of the moving object detection based on optical flow andneural network fusion.Themethod eliminates the influence caused bythe movement of thecamera to detect the target and has the ability to extract a complete moving target.Practical implications-It provides a powerful safeguard for target detection and targets the tracking application.Originality/value-The proposed method represents the fusion of optical flow and neural network to detect the moving object,and it can be used in new-generation intelligent monitoring systems.
出处 《International Journal of Intelligent Computing and Cybernetics》 EI 2016年第4期325-335,共11页 智能计算与控制论国际期刊(英文)
基金 This work was supported by the National Natural Science Foundation of China(No.61304223,No.61673209 and No.61533008) the Fundamental Research Funds for the Central Universities(No.NZ2015206 and No.NJ20160026).
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