针对传统人数统计方法因遮挡、光照变化导致准确率低的问题,提出一种适用于深度图的模拟降水分水岭算法(Depth map based Rainfalling Watershed Segmentation,D-RWS)。修复深度图并用混合高斯背景建模提取前景。利用D-RWS算法分割深度图中感兴趣的行人头部区域(Region Of Interest,ROI)。采用质心欧式距离最短法关联各帧中同一目标并跟踪计数。实验结果表明:提出的方法准确率能够达到98%以上,平均每帧处理时间为25 ms(40 f/s),准确率和实时性可满足实际应用的要求。
【英文摘要】
To solve problems such as occlusion and illumination changes that lead to low accuracy on conventional methods,a novel method D-RWS(Depth map based Rainfalling Watershed Segmentation)is proposed. Depth map is inpainted and foreground is extracted with the help of mixture of Gaussian background model. D-RWS algorithm is used to segment head area as Region Of Interest(ROI). People are tracked and counted by analyzing trajectories, which associated by minimal Euclidean distance between the centers. Experimenta...
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