联合局部专家估计目标子窗口

为了提高目标检测的效率和准确率, 提出一种估计目标子窗口的联合局部专家方法. 首先用局部专家交并集的方法滤除明显不包含目标的子窗口; 然后, 用局部专家向量空间模型中余弦定理的方法估计出包含目标的子窗口; 最后, 用局部专家非极大值抑制的方法从包含目标的子窗口中滤除重复包含同一目标的子窗口. 实验结果表明, 所提出的方法能快速准确地估计出包含目标的子窗口.

Joint local experts for measuring objectness of image proposal windows

In order to improve the efficiency and accuracy of object detection, the joint local experts method is proposed to estimate the objective windows by measuring how likely it is for an image proposal window to contain an object. Firstly, the proposal windows that do not contain any object obviously are filtered out by the local expert inter-union set. Then, the rest proposal windows that contain the object are measured by local expert cosine similarity. Finally, the objective windows are estimated by local expert non-maximum suppression from a large number of proposal windows that repeatedly contain the same object. Experiment results show that the proposed method is able to efficiently estimate the objective windows which accurately contain the object.