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• W2019304914 abstract "Motion detection, the process which segments moving objects in video streams, is the first critical process and plays an important role in video surveillance systems. Dynamic scenes are commonly encountered in both indoor and outdoor situations and contain objects such as swaying trees, spouting fountains, rippling water, moving curtains, and so on. However, complete and accurate motion detection in dynamic scenes is often a challenging task. This paper presents a novel motion detection approach based on radial basis function artificial neural networks to accurately detect moving objects not only in dynamic scenes but also in static scenes. The proposed method involves two important modules: a multibackground generation module and a moving object detection module. The multibackground generation module effectively generates a flexible probabilistic model through an unsupervised learning process to fulfill the property of either dynamic background or static background. Next, the moving object detection module achieves complete and accurate detection of moving objects by only processing blocks that are highly likely to contain moving objects. This is accomplished by two procedures: the block alarm procedure and the object extraction procedure. The detection results of our method were evaluated by qualitative and quantitative comparisons with other state-of-the-art methods based on a wide range of natural video sequences. The overall results show that the proposed method substantially outperforms existing methods with Similarity and F <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</sub> accuracy rates of 69.37% and 65.50%, respectively." @default.
• W2019304914 created "2016-06-24" @default.
• W2019304914 creator A5057852553 @default.
• W2019304914 creator A5071168688 @default.
• W2019304914 date "2014-01-01" @default.
• W2019304914 modified "2023-10-17" @default.
• W2019304914 title "Radial Basis Function Based Neural Network for Motion Detection in Dynamic Scenes" @default.
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• W2019304914 doi "https://doi.org/10.1109/tcyb.2013.2248057" @default.
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