Abstract
Detecting moving objects from video frames is one of the key techniques in computer vision. Background subtraction is a common way to detect moving objects at present. A new background subtraction algorithm is proposed in this paper. The algorithm describes backgrounds by a combination of hue and improved local binary pattern (LBP) texture and adopts the idea of Gaussian mixture model that uses multiple modes to represent background. In order to reduce matching complexity and satisfy real-time, the LBP texture feature vectors are simplified. Experiments show that the proposed algorithm can satisfy real-time in common resolution videos, can remove effectively the effect of shadow and can detect moving objects more accurately than others.
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Yuan, GW., Gao, Y., Xu, D., Jiang, MR. (2012). A New Background Subtraction Method Using Texture and Color Information. In: Huang, DS., Gan, Y., Gupta, P., Gromiha, M.M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2011. Lecture Notes in Computer Science(), vol 6839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25944-9_70
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DOI: https://doi.org/10.1007/978-3-642-25944-9_70
Publisher Name: Springer, Berlin, Heidelberg
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