Abstract
Based on the deficiencies of the Gaussian mixture model (GMM), the improvement is proposed in this paper. The image of video is partitioned into coarse Granularities by equivalence relation R, and the Quotient space can be obtained. Then the moving object is detected within it. The experiments show that the algorithm can improve the detection rate of the moving object without influencing to identify the object.
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Zhang, Y., Bai, Y., Zhao, S. (2010). Moving Object Detection Based on Gaussian Mixture Model within the Quotient Space Hierarchical Theory. In: Yu, J., Greco, S., Lingras, P., Wang, G., Skowron, A. (eds) Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science(), vol 6401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16248-0_104
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DOI: https://doi.org/10.1007/978-3-642-16248-0_104
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16247-3
Online ISBN: 978-3-642-16248-0
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