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...
| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2017
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| Online Access: | http://eprints.usm.my/39383/ http://eprints.usm.my/39383/1/CHUNG_SOON_ZHI_24_Pages.pdf |
| _version_ | 1848878730058924032 |
|---|---|
| author | Chung , Soon Zhi |
| author_facet | Chung , Soon Zhi |
| author_sort | Chung , Soon Zhi |
| building | USM Institutional Repository |
| collection | Online Access |
| 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%. |
| first_indexed | 2025-11-15T17:35:58Z |
| format | Thesis |
| id | usm-39383 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T17:35:58Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-393832019-04-12T05:25:06Z http://eprints.usm.my/39383/ Smart Digital Signage With Eye Tracking System 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 NonPeerReviewed application/pdf en http://eprints.usm.my/39383/1/CHUNG_SOON_ZHI_24_Pages.pdf Chung , Soon Zhi (2017) Smart Digital Signage With Eye Tracking System. Masters thesis, Universiti Sains Malaysia. |
| spellingShingle | TK1-9971 Electrical engineering. Electronics. Nuclear engineering Chung , Soon Zhi Smart Digital Signage With Eye Tracking System |
| title | 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_short | Smart Digital Signage With Eye Tracking System |
| title_sort | smart digital signage with eye tracking system |
| topic | TK1-9971 Electrical engineering. Electronics. Nuclear engineering |
| url | http://eprints.usm.my/39383/ http://eprints.usm.my/39383/1/CHUNG_SOON_ZHI_24_Pages.pdf |