Registration of Point Cloud Data from a Geometric Optimization Perspective

Simple item page
dc.contributor.authorMitra, Niloy J.en_US
dc.contributor.authorGelfand, Natashaen_US
dc.contributor.authorPottmann, Helmuten_US
dc.contributor.authorGuibas, Leonidasen_US
dc.contributor.editorRoberto Scopigno and Denis Zorinen_US
dc.date.accessioned2014-01-29T09:19:46Z
dc.date.available2014-01-29T09:19:46Z
dc.date.issued2004en_US
dc.description.abstractWe propose a framework for pairwise registration of shapes represented by point cloud data (PCD). We assume that the points are sampled from a surface and formulate the problem of aligning two PCDs as a minimization of the squared distance between the underlying surfaces. Local quadratic approximants of the squared distance function are used to develop a linear system whose solution gives the best aligning rigid transform for the given pair of point clouds. The rigid transform is applied and the linear system corresponding to the new orientation is build. This process is iterated until it converges. The point-to-point and the point-to-plane Iterated Closest Point (ICP) algorithms can be treated as special cases in this framework. Our algorithm can align PCDs even when they are placed far apart, and is experimentally found to be more stable than point-to-plane ICP. We analyze the convergence behavior of our algorithm and of point-to-point and point-to-plane ICP under our proposed framework, and derive bounds on their rate of convergence. We compare the stability and convergence properties of our algorithm with other registration algorithms on a variety of scanned data.en_US
dc.description.seriesinformationSymposium on Geometry Processingen_US
dc.identifier.isbn3-905673-13-4en_US
dc.identifier.issn1727-8384en_US
dc.identifier.urihttps://doi.org/10.2312/SGP/SGP04/023-032en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Computational Geometry and Object Modelingen_US
dc.titleRegistration of Point Cloud Data from a Geometric Optimization Perspectiveen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
023-032.pdf
Size:
1.48 MB
Format:
Adobe Portable Document Format
Download
Collections
SGP04: Eurographics Symposium on Geometry Processing