基于无监督在线学习实现视频遮挡边界检测

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为了检测视频序列中的遮挡边界,提出一种新颖的基于无监督在线学习的遮挡边界检测方法。该方法提取视频序列中待测帧的遮挡相关特征并计算其对应的时间长度,利用对冲算法思想并结合时间长度及不同遮挡特征求得待测帧中像素点的遮挡相关信息,利用各特征的遮挡相关信息进行投票,完成当前帧图像的遮挡边界检测。利用Online Boosting 思想以当前帧的检测结果来估计下一帧的特征投票权重,实现后续帧图像的遮挡边界检测。该方法通过在线学习思想改变不同特征的权重完成遮挡边界检测功能,无需预先获取视频序列的先验知识。实验结果表明,同已有方法相比,该方法具有较高的准确性和较好的通用性。
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