加速概率存在场目标检测的改进算法

概率存在场（POM）算法是一种多视角目标检测算法，其根据各视角对应的二值前景图像，估计检测场景中所有3D位置对应地面上存在目标的概率。当检测场地面积过大时，POM算法估计所有3D位置上存在目标的概率会十分耗时，拖累算法速度。提出了一种加快POM算法速度的方法：根据二值前景图像和3D位置信息，大幅减少POM算法需要处理的3D位置数量，从而提高算法速度。实验结果表明：在对算法检测结果影响很小的情况下，对于单目标和多目标检测场景，算法速度都得到了较大的提升。

Improved algorithm to accelerate target dectection of probabilistic occu-pancy map

Probabilistic occupancy map is an algorithm to detect targets on multiple views, it estimates the probability that target appears on each 3D position at the ground of detection scene based on the binary foreground images shot on each view. When the area of detection scene is large and therefore many 3D positions are to be detected, it will be very time-consuming to estimate the probability that target appears on each 3D position. A method to accelerate the POM algorithm is proposed in this paper： the number of 3D positions that POM algorithm needs to process is reduced substantially based on the binary foreground image and the corresponding 3D positions. The experimental results show that the speed of the algorithm can significantly improve with little reduction of detection accuracy when there is only one target or multiple targets appear in the scene appear.