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基于尺度不变Harris特征的准稠密匹配算法
Alternative TitleQuasi-dense matching based on scale invariant Harris feature
孙会超; 惠斌; 常铮
Department光电信息技术研究室
Source Publication计算机应用研究
ISSN1001-3695
2019
Volume36Issue:5
Contribution Rank1
Keyword尺度不变harris特征 准稠密匹配 局部非极大值抑制 三维重建
Abstract准稠密匹配是多视图三维重建的重要技术,其性能对重建结果至关重要。针对常用的Sift算法提取的种子点进行准稠密匹配正确率较低、重建效果不佳的问题,提出了一种基于尺度不变Harris角点特征的准稠密匹配算法。该算法首先在图像多尺度空间构造尺度不变Harris特征,并采用余弦距离测度对不同视图进行双向匹配;然后根据稀疏匹配获取种子点,采用最优最先匹配扩散策略进行准稠密扩散;最后采用局部非极大值抑制策略对匹配结果进行重采样。实验表明,本文算法提取的种子点既能够体现场景结构信息,又具有尺度不变特性,用于准稠密匹配能够提高匹配的效果和精度,是一种有效的用于三维重建的准稠密匹配算法。
Other AbstractQuasi-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.
Language中文
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/21619
Collection光电信息技术研究室
Corresponding Author孙会超
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院大学
3.中国科学院光电信息处理重点实验室
4.辽宁省图像理解与视觉计算重点实验室
Recommended Citation
GB/T 7714
孙会超,惠斌,常铮. 基于尺度不变Harris特征的准稠密匹配算法[J]. 计算机应用研究,2019,36(5).
APA 孙会超,惠斌,&常铮.(2019).基于尺度不变Harris特征的准稠密匹配算法.计算机应用研究,36(5).
MLA 孙会超,et al."基于尺度不变Harris特征的准稠密匹配算法".计算机应用研究 36.5(2019).
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