Applying distribution of feature points to detect multiple plane
Applying distribution of feature points to detect multiple plane
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DOI：
10.1504/ijguc.2012.045710
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发表时间：
2012-03
期刊：
影响因子：
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通讯作者：
Lugang Zhao;Chengke Wu
中科院分区：
文献类型：
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作者：
Lugang Zhao;Chengke Wu
针对图像序列中多个平面区域的快速检测问题，提出了一种新的算法。该方法首先利用RANSAC算法检测出一个占主导地位的单应性，然后基于单应性约束计算出两幅图像对应的极点，并将所有匹配特征点分成两个集合。当基于RANSAC再次检测多个平面对应的单应性时，只需从已分类的特征点中选取三对特征点，即与一对极点一起定义待确定的平面单应性模型，这样可以提高检测效率。仿真和真实的实验结果表明，该算法对特征失配具有较强的鲁棒性，适用于立体图像和运动序列图像。
For detecting multiple planar regions rapidly in the image sequence, this paper proposed a novel algorithm. First of all, the method uses RANSAC to detect a dominant homography, then, it calculates the poles corresponding to the two images based on homography constraint and classifies all the matching feature points into two sets. When we detect the homography corresponding to more planes based on RANSAC once more, only three pairs of feature points should be selected from the classified feature points, that is define the to-be-determined plane homography model together with a pair of poles, and this can improve the detection efficiency. Simulation and real experiment results show that the proposed algorithm is robust to the existence of mismatched features and is applicable to either stereo or motion sequence images.