Abstract
Background modeling method is one of the most commonly methods for target detection. Gaussian mixture model (GMM) is a widely used background modeling method which can get good performance in video of surveillance scenes. However, when the GMM is directly applied to the detection of small moving targets, it may cause problems such as incomplete and missing detection of the target contour. Therefore, we propose a new background modeling method by using skew normal mixture model (SNMM). A skew normal mixture model is established at each pixel position in frames of video. After updating the frames of video, the parameters of the background model SNMM are updated, and the detection of small moving target is performed. Experimental results show that the SNMM can obtain better contour of the small moving targets in videos than the GMM.
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Acknowledgments
This paper has been partly supported by Xi’an science and technology planning project (No. 201805037YD15CG21(7)), China.
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Shao, Y., Dai, F. (2019). Detection of Small Moving Targets in Videos Using Skew Normal Mixture Model. In: Wang, Y., Huang, Q., Peng, Y. (eds) Image and Graphics Technologies and Applications. IGTA 2019. Communications in Computer and Information Science, vol 1043. Springer, Singapore. https://doi.org/10.1007/978-981-13-9917-6_31
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DOI: https://doi.org/10.1007/978-981-13-9917-6_31
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