Background Modeling Using Temporal-Local Sample Density Outlier Detection

作者：Zeng Wei^*; Yang Mingqiang; Wang Feng; Cui Zhenxing

来源：1st International Conference on Computer Vision and Image Processing (CVIP), 2016-02-26 to 2016-02-28.

DOI：10.1007/978-981-10-2104-6_1

• Background modeling
• Temporal-local sample density
• Outlier detection

Although researchers have proposed different kinds of techniques for background subtraction, we still need to produce more efficient algorithms in terms of adaptability to multimodal environments. We present a new background modeling algorithm based on temporal-local sample density outlier detection. We use the temporal-local densities of pixel samples as the decision measurement for background classification, with which we can deal with the dynamic backgrounds more efficiently and accurately. Experiment results have shown the outstanding performance of our proposed algorithm with multimodal environments.

• 单位
  山东大学