.png){kind=icon}
返回
Registering sets of points using Bayesian regression
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2012.02.018.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This work addresses the problem of non-rigid registration between two 2D or 3D points sets as a novel application of Relevance Vector Machines (RVM). An iterative framework is proposed which consists of two steps: at first, correspondences between distinct points are estimated by the Hungarian algorithm and then a regression procedure based on a Bayesian linear model (RVM) maps the two sets of points. By these means, a large variety of transformation is captured without imposing any prior knowledge on the form of the point sets. The proposed algorithm provides a smooth transformation even if the correspondence between the points in the two sets contains erroneous matches. The algorithm was successfully evaluated on sets of points with varying difficulty and favorably compared with state-of-the-art methods in cases of noise. (c) 2012 Elsevier B.V. All rights reserved.
Keyword:
Registration of sets of points
Relevance vector machine (RVM)
Hungarian algorithm
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
引用论文
.png){kind=icon}
分享收藏分享收藏
查看更多内容