3D Objects Recognition Using Artificial Neural Networks

Abstract

The recent advances in computational processing and the low prices of sensors able to capture three-dimensional information have contributed for the progress of computer vision researches involving 3D data and 3D images. Object recognition allows us to develop complex applications for intelligent mobile robotics, augmented reality, systems for the visually impaired, among other applications. In this context, this paper presents a method for recognizing and classifying objects which are represented in three dimensions through depth maps. The data used in this study comes from the "UW RGB-D Object Dataset" from University of Washington, which is available online and is largely used to evaluate 3D object classifiers. This object database is composed of depth maps captured by the Microsoft's Kinect sensor. The obtained results are promising and contribute positively to the computer vision area.