A Smart-Glasses-based Augmented Reality Assisted System

碩士 === 國立中央大學 === 資訊工程學系 === 106 === Recently, the application of augmented reality has become more and more prevalent. With the advent of smart-glasses, the related research of augmented reality has been grown vigorously. Therefore, this dissertation proposes an augmented reality assisted system wh...

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Bibliographic Details
Main Authors: Hsiang-Ling Chang, 張湘菱
Other Authors: Mu-Chun Su
Format: Others
Language:zh-TW
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/5gpbj4
Description
Summary:碩士 === 國立中央大學 === 資訊工程學系 === 106 === Recently, the application of augmented reality has become more and more prevalent. With the advent of smart-glasses, the related research of augmented reality has been grown vigorously. Therefore, this dissertation proposes an augmented reality assisted system which will be set up on the smart-glasses. By setting the system on the smart glasses, the user will be able to use the system in personal perspective. There are three main features in the system.(1)With a set of simple procedure, the system will set up dataset of objects on the device. Moreover, the system can identify the object and its position on the device automatically by using the Mask R-CNN method.(2)By capturing pointing gesture from the image and analyzing the pointing direction, the system will display the object information according to the finger pointing direction.(3)Using the calibrating object to analyze the rotation angles of virtual tools. The aim of this system is to provide a system that can assist technicians in training. With the finger pointing, the system can show the object information which the user wants to know on the smart-glasses immediately. According to the results of the experiments, the percentage of recognition of object detection is 95.5%, the Kappa value of recognition of gesture detection is 0.93, and the average time for detecting pointing gesture is 0.26 seconds. Furthermore, even under different light, the proportion of accuracy of the pointing analysis is up to 79%. Based on the results of the experiments, it was proved that the method which was applied in this dissertation is applicable.