中文摘要：

传统的准稠密对应点匹配算法大都是针对一般场景开发的,未考虑场景的结构特点.为此,针对结构化场景提出一种基于平面单应约束的准稠密匹配方法.首先采用基于仿射不变量的方法检测和匹配稀疏平面种子区域,然后根据平面间的几何约束和对应点相似性约束,利用区域增长的方法实现准稠密扩散匹配.最优种子区域优先扩散策略的应用大大减小了初始错误种子区域对扩散过程的影响,而对不可靠扩散点的后处理也有效地提高了最终三维重建的精度.实验结果表明,相比传统的准稠密匹配方法,对于结构化场景,采用文中方法更加精确和稳定.

英文摘要：

Conventional quasi-dense matching algorithms are designed for general scene structures.A novel quasi-dense matching method is proposed for structured scenes,which is based on plane induced homography.First,sparse planar seed regions are detected and matched by using affine invariant detector and matcher.Then region growing algorithm is employed to propagate seed region to its neighboring pixel by using the constraints of both planar homography and similarity measure.The best-first strategy is used which make our algorithm robust to initial sparse match outliers.Further more,more accurate reconstruction can be achieved by post-processing of unreliable matches.Experiment results show that our algorithm is more stable and accurate than conventional algorithms.