A Study on the Robustness of Shape Descriptors to common scanning artifacts

Text Complet
Study-on-the-Robustness.pdf embargoed access
Sol·licita còpia a l'autor de l'article
En omplir aquest formulari esteu demanant una còpia de l'article dipositat al repositori institucional (DUGiDocs) al seu autor o a l'autor principal de l'article. Serà el mateix autor qui decideixi lliurar una còpia del document a qui ho sol•liciti si ho creu convenient. En tot cas, la Biblioteca de la UdG no intervé en aquest procés ja que no està autoritzada a facilitar articles quan aquests són d'accés restringit.
Compartir
Registration is a fundamental problem in a myriad of applications ranging from heritage reconstruction to industrial applications. Descriptors are an important part of the registration pipeline as well as a very active research field. However, the sets used to illustrate descriptor performance have often undergone several preprocessing steps such as noise filtering, hole filling or outlier removal. These steps simplify the problem but are not readily available in many applications. In this paper we compare the performances of 4 state of the art shape descriptors: SHOT [1], Spin Image [2], FPFH [3] and 3DSC [4]. Experiments were carried out with real as well as synthetic data paying special attention to issues commonly present in real data (noise, outliers and low overlap). The method obtaining a best result overall is SHOT, based mostly on the results with synthetic data. Experiments with real data showed how state of the art descriptors are not yet able to produce optimal results in the most challenging scenarios ​
​Tots els drets reservats