Block-matching-based motion field generation utilizing directional edge displacement
Block-matching-based motion field generation utilizing directional edge displacement
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DOI：
10.1016/j.compeleceng.2008.11.017
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发表时间：
2010-07
期刊：
影响因子：
--
通讯作者：
Hitoshi Hayakawa;T. Shibata
中科院分区：
文献类型：
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作者：
Hitoshi Hayakawa;T. Shibata
提出了一种基于边缘标志直方图块匹配的运动场生成算法，并将其应用于运动识别系统。使用边缘标志代替像素强度使得算法对光照变化具有鲁棒性。为了有效地检测感兴趣的局部运动，引入了一种新的自适应帧间隔调整方案，该方案只累积帧中存在的局部运动引起的边缘标志并利用其进行块匹配。将这些边缘标志投影到x轴和y轴上生成直方图，并通过直方图匹配确定x和y方向上的运动。因此，最佳匹配搜索的计算成本大大降低。本文还提出了一种运动场的矢量表示，称为投影主运动分布（PPMD）。将该方法应用于隐马尔可夫模型（hmm）的初步运动识别实验，验证了其有效性。此外，本文还证明了所提出的运动场生成方法相对于简单光流和传统的基于像素强度的块匹配方法的优势。
A motion field generation algorithm using block matching of edge flag histograms has been developed aiming at its application to motion recognition systems. Use of edge flags instead of pixel intensities has made the algorithm robust against illumination changes. In order to detect local motions of interest effectively, a new adaptive frame interval adjustment scheme has been introduced in which only the edge flags due to local motions present in the frame are accumulated and utilized in block matching. These edge flags are projected onto x and y axes to generate histograms and the motion in x and y directions are determined by histogram matching. As a result, the computational cost for best match search has been substantially reduced. A vector representation of the motion field, which is called projected principal-motion distribution (PPMD), has also been proposed. It was applied to preliminary motion recognition experiments using Hidden Markov Models (HMMs) and its effectiveness has been confirmed. Moreover the advantage of the proposed motion field generation method over the simple optical flow as well as the conventional block matching method using pixel intensities has been demonstrated.