一种快速的视频序列运动分割方法

提出一种视频序列运动分割的实时方法，该方法通过两次背景更新提取运动前景，其中长程背景更新检测噪声运动区域，并将长时间停留在场景中的物体纳入背景范围，短程背景更新利用单高斯分布模型实现对光线缓慢变化的适应。采用基于颜色空间的方法实现对阴影的消除，通过投影分割提取出不同的运动目标。试验证明该方法能够快速、精确地实现视频序列中多个运动目标的分割，消除背景噪声运动、目标阴影以及场景变化的影响。

High Speed Method for Motion Segmentation in Video Sequences

This paper proposes a real-time motion segmentation method for video sequences. The background image is reconstructed by using the long-term and short-term background updating algorithms. The long-term updating algorithm detects the noisy motion regions and the ghosts (detected as in motion but not corresponding to any real moving object), while the short-term updating algorithm models the background pixel values with single Gaussian distributions to deal with slow lighting changes. The shadows are removed via the color space based approach. Different targets are located with the projection approach. Experimental results prove that the presented method is robust to background noisy motions, shadows and scene changes, and can segment multiple objects precisely and quickly.