中文摘要：

采用多摄像机多平面单应前景映射融合的方法可以减小目标遮挡所造成的影响并提高目标检测的准确性和可靠性。采用传统的前景图单应变换是一个图像级的运算,需要将前景图中的全部像素逐一投影到参考视角中。为了消除透视效应产生空洞区域,还需根据分辨率较高的参考视角反映射的方法确定前景投影图。由于计算量较大,处理无法应用到实时目标检测中。该文提出了一种前景轮廓多边形顶点映射的方法,首先对在单摄像机中检测出的前景进行多边形逼近,只对前景多边形的顶点进行单应映射,最后在参考视角中根据映射顶点进行前景重构,提高前景映射的运算速度以满足多摄像机前景融合实时目标检测。实验中,多边形顶点法与传统法、轮廓法、矩形框法进行了比较。实验表明,重构的前景映射图不仅可以有效地逼近图像级单应变换的前景映射图,而且在运动目标大小不同的情况下,多摄像机前景融合目标检测的运算速度可以分别提高约12和69倍。

英文摘要：

Multi-camera and multi-plane foreground fusion approach can relieve the effects of occlusion and improve the accuracy and robustness of moving object detection. The traditional homography mapping is an image-level transformation which projects each pixel in the binary foreground image into a reference view. To avoid perspective openings or holes which are generated during the mapping from the camera view to the top view,the number of the pixels in the homography mapping is decided by the resolution of the top view,which is usually higher than that of the camera view. The slow speed has dissuaded the foreground homography mapping from real-time applications. A foreground polygon approximation method is proposed. After the foreground regions are identified in a camera view,each foreground region is approximated by a polygon and only the vertices of the polygon are projected to the reference view through homography mapping. Then the projected foreground region,which is rebuilt in the reference view,is utilized in real-time moving object detection with multiple cameras. To evaluate the performance,the proposed polygon approximation method has been compared with the contour based method and the boundingbox based method. The experimental results have shown that the proposed algorithm can produce competitive results in comparison with those using foreground bitmap mapping. Considering the differences of moving objects＇ size,the processing speed is about 12 and 69 times faster than the bitmap mapping method.