http://onlinelibrary.wiley.com/doi/10.1111/cgf.12732/full 文章链接
https://github.com/PointCloudLibrary/pcl/pull/1614 源码pull request
Pairwise Registration by Local Orientation Cues
只是提交了pull request，还没有正式的merge到pcl的源码master里，不过看文章，效果不错。值得测试下。
Abstract[size=1.6em]Inspired by recent work on robust and fast computation of 3D Local Reference Frames (LRFs), we propose a novel pipeline for coarse registration of 3D point clouds. Key to the method are: (i) the observation that any two corresponding points endowed with an LRF provide a hypothesis on the rigid motion between two views, (ii) the intuition that feature points can be matched based solely on cues directly derived from the computation of the LRF, (iii) a feature detection approach relying on a saliency criterion which captures the ability to establish an LRF repeatably. Unlike related work in literature, we also propose a comprehensive experimental evaluation based on diverse kinds of data (such as those acquired by laser scanners, Kinect and stereo cameras) as well as on quantitative comparison with respect to other methods. We also address the issue of setting the many parameters that characterize coarse registration pipelines fairly and realistically. The experimental evaluation vouches that our method can handle effectively data acquired by different sensors and is remarkably fast.
| 
|小黑屋|点云技术相关产学研社区
( 陕ICP备13001629号 )
发表于 2016-6-1 09:27:44