提取移动相机拍摄视频中的前景时，采用基于稠密光流或像素点轨迹的算法估算相机运动会造成算法非常耗时，为此提出一种简单有效的实时视频背景减除算法。首先用基于超像素的区域增长预处理算法得到可能是前景的超像素；然后基于分块相对光流的背景特征点筛选算法来估算相机运动；最后检查光流与相机运动的一致性，得到背景减除的最终结果。实验结果表明，该算法可以实时处理大小为640×480像素的视频，且前景检测准确度优于同类算法。%To extract moving foreground from a video captured by a moving camera, dense optical flow or point trajectories are often introduced to handle the camera motion, but they make the moving foreground extraction very slow. To solve this problem, a simple and effective real-time algorithm for moving camera background sub-traction is proposed. Firstly, a superpixel-based region growing algorithm is proposed to preprocess the input im-age frames. Then, the camera motion is estimated in a block-based fashion with a background feature-point fil-tering method based on the relative flow. Finally, the background subtraction result is obtained via a verification process based on the accordance of the optical flow and the camera motion. Experimental results show that the proposed algorithm can process a 640×480 video in real-time. In addition, the foreground detection accuracy of the proposed algorithm outperforms other real-time moving foreground extraction methods.
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