关键词: 宽基线图像, 最大稳定极值区域, 仿射传递, 自适应支持加权

Abstract: Textures of outdoor buildings are generally repetitive and locally insufficient. Previous quasi-dense matching methods do not work well on such wide baseline images because the obtained initial seeds are not enough and have matching ambiguity when propagating. This paper proposes an efficient quasi-dense matching algorithm for wide baseline images of building scene, of which MSERDoG(maximally stable extremal regions on difference of Gaussian space) is given to obtain more initial seed matches, and then affine propagation with adaptive support- weight score is used to have better quasi-dense matches. Experiments demonstrate that the proposed algorithm is efficient and satisfactory.

Key words: wide baseline images, maximally stable extremal regions on difference of Gaussian space (MSERDoG), affine propagation, adaptive support-weight