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In this paper, a method of recognizing a 3D object using a machine learning algorithm is described. 3D object data sets consisting of geometric polygons are analyzed by Keras, a deep learning API that learns composition rules of data sets. A 3D object can be recognized by applying a composition rule to the object. Data sets for various types of objects have been experimented with. 100 objects per shape were used to learn the rules and different objects were used for evaluating the rules. Seven types of 3D objects were experimented with. In addition, evaluation results for different numbers of 3D objects were compared.

3D Object Recognition Using X3D and Deep Learning