Counting Pedestrians Based on Weight-Minkowski-Dimension and Gaussian Process Regression
A method is proposed to count the number of pedestrians based on Weight-Minkowski-Dimension and Gaussian process regression for fixed cameras surveillance.First of all,the crowd foreground was extracted using Gaussian mixture model,and then the Weight-Minkowski-Dimension,which count the boxes with weights that was calculated based on linear interpolation,was extracted in the binary image of foreground edge,and finally the number of crowd was predicted by and Gaussian process regression.And we evaluate the algorithm both in Fudan dataset and Pets2009 dataset.Experimental result shows that the Weight-Minkowski-Dimension not only responds the change of the crowd number,but also eliminates the influence of perspective distortions,thereby improves estimation accuracy.On the other hand,it performs better in crowded scene.
Counting pedestrians Gaussian mixture model Weight-Minkowski-Dimension Gaussian process regression
Zhang Junjun Shi Zhiguang Li Jicheng Zhang Feng Ye Xin
ATR Key Laboratory, College of Electronic Science and Engineering, National University of Defense Technology, Changsha Hunan 410073, China
国际会议
重庆
英文
168-174
2016-03-21（万方平台首次上网日期，不代表论文的发表时间）