基于尺度不变Harris特征的准稠密匹配算法

Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-19 Cooperative journals: 《计算机应用研究》

孙会超 惠斌 常铮

Abstract： Quasi-dense matching is widely used in multi-view 3D reconstruction, and it is important for reconstruction results. Aiming at the quasi-dense matches diffused by the seed points extracted from Sift algorithm are less accurate, this paper proposed a quasi-dense matching algorithm based on scale invariant Harris corners. Firstly, it structured the scale invariant Harris features in multi-scale space, and the feature sets between different views are bidirectional matched by cosine distance similarity measure; Then the seeds selected from the initial matches are applied in quasi-dense matching algorithms by best and first propagation strategy; Finally, a local non-maximum suppression strategy is applied to resampling the quasi-dense matches. Experiments show that the seeds extracted by this algorithm can not only reflect the scene structure information, but also have scale invariant characteristics. And for quasi-dense diffusion, the matching effect and accuracy can be improved, and it is an effective quasi-dense matching algorithm for 3D reconstruction.

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