Development Android Application for Visualization of Technical Characteristics Based on Augmented Reality and Machine Learning Methods

Abstract

Nowadays the number of electronic devices has increased as well as their complexity. At the same time only few people are reading user guides for these devices. Moreover, in certain cases even no guides are provided by the manufacturer. Therefore there is a large number of cases when people use such devices incorrectly. This issue could be possibly solved with a system automatically recognizing the type of the device. Such system could provide all necessary user information about that device. This article suggests one of possible implementations of such device type recognition system. It recognizes type of device in an unsupevised way and shows main characteristics and user guides for the recognized gadget. Our approach for constructing such system relies on machine learning methods since greedy search for an object pattern is not efficient, as it was found out by recent scholarly works. Moreover, automatic object patterns classifiers show higher performance in this task and allow to scale the system to various kinds of input data. The algorithms that we are using for object classification are based on feature extraction from an graphical representation of the object look. This representation is usually proposed in an digital photography format. We consider our study as the first work towards automated defining characteristics of a device based on its graphical representation.