Smart Digital Signage With Eye Tracking System

Digital signage is a more effective advertising solution compared to the traditional sign board since it is able to show multimedia contents and the advertising information can be easily updated. Current digital signage system has limited user interactive capability. Besides that, current system als...

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Main Author: Chung , Soon Zhi
Format: Thesis
Language:English
Published: 2017
Subjects:
Online Access:http://eprints.usm.my/39383/1/CHUNG_SOON_ZHI_24_Pages.pdf
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spelling my-usm-ep.393832019-04-12T05:25:06Z Smart Digital Signage With Eye Tracking System 2017 Chung , Soon Zhi TK1-9971 Electrical engineering. Electronics. Nuclear engineering Digital signage is a more effective advertising solution compared to the traditional sign board since it is able to show multimedia contents and the advertising information can be easily updated. Current digital signage system has limited user interactive capability. Besides that, current system also lacks a way to collect viewer’s behaviour for analytic purposes. With the advancement of information technology, smart signage system allows some interactions between the viewer and the signage. In this project, a smart digital signage system which is capable of interaction between a user’s mobile device and the signage system is proposed. The user’s application on the mobile device provides a convenience way for navigating and storing the digital advertisements shown on the signage system instead of having paper brochure. Besides interactive capability, the proposed system is also able to detect faces and eyes to count the users viewing duration for each advertisement shown on the display. The faces and eyes detection were implemented using Haar Cascaded classifier available in the OpenCV library. A sanity checking algorithm is proposed to filter out the wrong detected eyes and improve the overall detection rate. Test results showed that the implemented face and eyes detection function can achieve 82.5% of true positive rate and 17.5% of false negative rate. Test on the complete system showed that the proposed smart signage system is able to work as expected. It is able to collect the users’ viewing duration for each advertisement with an average error of less than 12%. 2017 Thesis http://eprints.usm.my/39383/ http://eprints.usm.my/39383/1/CHUNG_SOON_ZHI_24_Pages.pdf application/pdf en public masters Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Elektrik dan Elektronik
institution Universiti Sains Malaysia
collection USM Institutional Repository
language English
topic TK1-9971 Electrical engineering
Electronics
Nuclear engineering
spellingShingle TK1-9971 Electrical engineering
Electronics
Nuclear engineering
Chung , Soon Zhi
Smart Digital Signage With Eye Tracking System
description Digital signage is a more effective advertising solution compared to the traditional sign board since it is able to show multimedia contents and the advertising information can be easily updated. Current digital signage system has limited user interactive capability. Besides that, current system also lacks a way to collect viewer’s behaviour for analytic purposes. With the advancement of information technology, smart signage system allows some interactions between the viewer and the signage. In this project, a smart digital signage system which is capable of interaction between a user’s mobile device and the signage system is proposed. The user’s application on the mobile device provides a convenience way for navigating and storing the digital advertisements shown on the signage system instead of having paper brochure. Besides interactive capability, the proposed system is also able to detect faces and eyes to count the users viewing duration for each advertisement shown on the display. The faces and eyes detection were implemented using Haar Cascaded classifier available in the OpenCV library. A sanity checking algorithm is proposed to filter out the wrong detected eyes and improve the overall detection rate. Test results showed that the implemented face and eyes detection function can achieve 82.5% of true positive rate and 17.5% of false negative rate. Test on the complete system showed that the proposed smart signage system is able to work as expected. It is able to collect the users’ viewing duration for each advertisement with an average error of less than 12%.
format Thesis
qualification_level Master's degree
author Chung , Soon Zhi
author_facet Chung , Soon Zhi
author_sort Chung , Soon Zhi
title Smart Digital Signage With Eye Tracking System
title_short Smart Digital Signage With Eye Tracking System
title_full Smart Digital Signage With Eye Tracking System
title_fullStr Smart Digital Signage With Eye Tracking System
title_full_unstemmed Smart Digital Signage With Eye Tracking System
title_sort smart digital signage with eye tracking system
granting_institution Universiti Sains Malaysia
granting_department Pusat Pengajian Kejuruteraan Elektrik dan Elektronik
publishDate 2017
url http://eprints.usm.my/39383/1/CHUNG_SOON_ZHI_24_Pages.pdf
_version_ 1747820745683107840