Myeyeswear - Mobile commerce application with augmented reality for eyewear fitting / Muhammad Solehin Suhalwi
The development of mobile communication technology and the m-commerce sector has led to a rapid growth of mobile commerce applications in recent years. However, most of m-commerce platform does not have features of try the product in person before making a purchase. With the use of augmented reality...
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| Format: | Thesis |
| Language: | English |
| Published: |
2022
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| Online Access: | https://ir.uitm.edu.my/id/eprint/104176/1/104176.pdf https://ir.uitm.edu.my/id/eprint/104176/ |
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| Summary: | The development of mobile communication technology and the m-commerce sector has led to a rapid growth of mobile commerce applications in recent years. However, most of m-commerce platform does not have features of try the product in person before making a purchase. With the use of augmented reality technology, users can have an immersive shopping experience. The objectives of this project are to identify the requirements of the MyEyewear mobile application, to design the MyEyewear mobile application and to develop the MyEyewear mobile application. This project is expected to be beneficial for the public users who want to purchase eyewear online. MyEyewear is an Augmented Reality app that allows users to virtually try on eyewear before deciding to buy the eyewear. This application has features such as login, add to cart, view order history, search product and delete order. This app also enables the users to fit the eyewear on their face virtually with the implementation face detection of Augmented Reality through the try-on feature. This project used Mobile Application Development Life Cycle (MADLC) as a methodology approach to develop this app. The technique utilized in this project is the face detection augmented reality. This project will project virtualized eyewear on the user’s face by pointing the smartphone’s camera to the face with face tracking method. It also can increase the user satisfaction where they can access and wear the eyewear directly on their mobile phone using the mobile camera with the AR technology on the application. The testing result for the application involved 10 users which the score of 76.6 based on the System Usability Scale (SUS). Future recommendation is to improve the machine learning in detecting the user face which to precisely detect all different type of human faces which to make the augmented reality features accurate. |
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