A Study of 3D Shape Similarity Search in Point Representation by Using Machine Learning

Abstract

Abstract3D shape similarity seach have been studied for detecting or finding a specified 3D model among 3D CAD model database. We propose to use 3D point data for the search, because it has become easier to obtain 3D point data by photographs. CAD data is converted into 3D point data in advance. Then, using machine learning, we attempt to match those data with the 3D point data acquired in the field. It can be expected that the accuracy of matching is improved by directly handling 3D data. As a preliminary trial, we have tried to clasify 10 kinds of chair models in represented as 3D point data with a machine learning approach. It was suggested that 3D shape matching between 3D point data is possible by our proposed method as the result.