摄像机运动情况下的运动对象检测(英文)

Fast Moving-Object Detection with a Moving Camera

在监控应用中 ,由于场景是已知的 ,因此可以使用背景减去法检测运动对象 .当摄像机进行扫描和倾斜运动时 ,需要使用多个图像帧才能完整地表示监控场景 .如何组织和索引这些背景帧属于摄像机跟踪问题 .提出一种无需摄像机标定的背景帧索引和访问方法 .这一方法需要使用图像配准技术估计图像初始运动参数 .提出一种屏蔽外点的图像配准算法 ,综合利用线性回归和稳健回归快速估计初始运动参数 .为了快速计算连续帧之间的运动参数 ,提出一种基于四参数模型的优化算法 .利用非参数背景维护模型抑制虚假运动象素 .

In the surveillance applications, the scenes are known. So background subtraction can be used to detect the moving pixels. As a panning-tilting camera is used, several video frames are needed to represent the scene of surveillance. How to organize and index these frames to represent the background of surveillance belongs to the problem of camera tracking. We propose a simple camera tracking approach that makes it easy to determine a frame as the current background without the need of camera calibration. This approach needs estimating the initial motion parameters by the technology of image registration. We propose a fast and robust method for registering the current frame and the background frame, by combining the linear regression and the robust regression on the basis of masking the outliers. To fast estimate the motion parameters between two adjacent frames, an optimized algorithm for motion tracking with the 4-parameter model is given. A non-parametric model of background maintenance is introduced to reject the false alarms. Finally, we present experimental results in two applications demonstrating the effectiveness and efficiency of our methods.