IEEE Trans Image Process - On averaging multiview relations for 3D scan registration.

Tópicos

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Resumo

In this paper, we present an extension of the iterative closest point (ICP) algorithm that simultaneously registers multiple 3D scans. While ICP fails to utilize the multiview constraints available, our method exploits the information redundancy in a set of 3D scans by using the averaging of relative motions. This averaging method utilizes the Lie group structure of motions, resulting in a 3D registration method that is both efficient and accurate. In addition, we present two variants of our approach, i.e., a method that solves for multiview 3D registration while obeying causality and a transitive correspondence variant that efficiently solves the correspondence problem across multiple scans. We present experimental results to characterize our method and explain its behavior as well as those of some other multiview registration methods in the literature. We establish the superior accuracy of our method in comparison to these multiview methods with registration results on a set of well-known real datasets of 3D scans.

Resumo Limpo

paper present extens iter closest point icp algorithm simultan regist multipl d scan icp fail util multiview constraint avail method exploit inform redund set d scan use averag relat motion averag method util lie group structur motion result d registr method effici accur addit present two variant approach ie method solv multiview d registr obey causal transit correspond variant effici solv correspond problem across multipl scan present experiment result character method explain behavior well multiview registr method literatur establish superior accuraci method comparison multiview method registr result set wellknown real dataset d scan

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