Multi-Person Tracking using Overlapping Silhouette Templates for a Mobile Robot

我们开发了一种将人物形状的深度模板应用于密集深度图像的跟踪方法。利用考虑人物在图像中的重叠情况的重叠轮廓模板实现了精确、稳定的跟踪。采用基于核密度估计的近似似然图来减少图像比较的次数。我们在普通人较多的真实环境中进行了具体的人跟随实验，并对结果进行了分析。

We developed a tracking method which uses depth templates of person shape applied to a dense depth image. An accurate, stable tracking is realized by using overlapping silhouette templates which consider how persons overlap in the image. The number of image comparison is decreased by using an approximated likelihood map based on kernel density estimation. We performed experiments of specific person following in real environment where many ordinary people exist, and analyzed the results.