E-COMMERCE WEB APPLICATION WITH AUGMENTED REALITY (AR)
Suman Zareen1 , Tuba Masood2, Pathan Ahmed khan3
1, 2 UG Scholar , Dept. of CSE,ISL Engineering College, Hyderabad
3Associate Professor, Dept. of CSE ,ISL Engineering College, Hyderabad
This project exhibits an image and object processing methodology for Virtual Dressing Room (VDR) applications that run on the personal computer in the form of e-commerce web application. The proposed user-friendly application requires user image to be pre-processed. Haar Cascade classifiers are an effective way for object detection .Haar Cascade is a machine learning-based approach where alot of positive and negative images are used to train the classifier.
Considering the above extracted keypoints augmented reality will be used to superimpose the products over the buyer’s live picture. Proposed VDR is software implemented using OpenCV built in functions. OpenCV is a cross-platform library using which we can develop real-time computer vision applications.It mainly focuses on image processing analysis including features like face detection and object detection.
Having witnessed the influence of the internet on shopping, it will be a grave mistake to ignore the benefits that augmented reality brings to the industry of online shopping. As online retail seeks to improve its conversion rates and bolster more revenue, the benefits of augmented reality cannot be overstated. Augmented reality offers various businesses the chance to create a more interactive shopping experience with their customers as it offers the opportunity to virtually try the product they want to purchase.
In general, technology can benefit people’s lives. For example, during the past 20 years, with the development of computer and Internet technology, e-commerce and online shopping have rapidly progressed, due to the convenience that they provide consumers. E-commerce websites, such as Amazon.com, Dell.com, and eBay.com, have become an integral part of many shoppers’ lives.
However, according to most shoppers’ experiences, e-commerce and online shopping are still not able to fully replace onsite shopping, especially for products like clothing, shoes, jewellery, and furniture. For many such products, onsite shopping has many distinct advantages over online shopping. One of the main advantages of onsite shopping is that it usually provides more direct interaction with the actual product. In contrast, conventional online shopping websites often cannot provide enough information about a product for the customer to make an informed decision before checkout. Onsite shoppers frequently engage in some sort of interaction with their potential purchase to discover the scent, texture, appearence, and/or sound characteristics of a product before buying it. Such experience is often impossible with current online purchases.
However, technology is progressing. In particular, Augmented Reality (AR), an emerging Human-Computer Interaction technology, which aims to mix or overlap computer generated 2D or 3D virtual objects and other feedback with real world scenes, shows great potential for enhancing e-commerce systems. Unlike VR, which replaces the physical world, AR enhances physical reality by integrating virtual objects into the physical world. The virtual object becomes, in a sense, an equal part of the natural environment. This chapter presents a new type of e-commerce system, AR e-commerce, which visually brings virtual products into real physical environments for user interaction. The new approach gives customers a chance to “try” a product at home or in another use environment. The chapter presents development of a prototype AR e-commerce system and provide suggestions for improvement. Overall results of the study shows that the AR e-commerce system can help customers make better purchasing decisions.
2.1 VR in E-commerce:
Virtual reality (VR) is a computer-simulated environment that allows users to manipulate 3D virtual models online. Recently, researchers have been using VR in e-commerce to provide consumers with a new type of shopping experience by interacting with virtual product models. Hughes et al (2002) presented an adaptive navigation support system for using a virtual environment for online shopping. Sanna et al. (2002) presented a VR ecommerce system based on VRML. They used QuickTime 3D to generate 360-degree image based immersive backgrounds and an animated virtual human to help online shoppers navigate through their e-commerce environment. Bhatt (2004) analyzed the interactivity, immersion, and connectivity of several major VR-ecommerce websites, such as amazon.com, ebay.com, and schwab.com. Daugherty et al. (2005) conducted five experiments to study the usability of VR for e-commerce. Their results showed that users acquired more information about products when using a VR-based e-commerce system than when using traditional website tools. Fomenko (2006) developed a tool for creating online VR shops, which also gave domain experts more control during the website development process. With Fomenko’s tool, developers can use high-level concepts to model and semi-automatically generate a complete VR shop.
2.2 Moving from VR to AR:
Although prior studies show that VR can enhance e-commerce, by providing more product information through enhanced human-computer interaction, current VR methods for ecommerce still only provide scaled virtual product models displayed on traditional computer screens. New, more advanced, methods are needed to provide consumers with more realistic product models, with respect to size, customer experience, and user interaction.
AR is a technology which can mix or overlap computer-generated virtual objects with realworld scenes or objects. Unlike VR, which experientially replaces the physical world, AR enhances physical reality by integrating virtual objects into a physical scene. Generated virtual objects become, in a sense, an equal part of the natural environment. In recent years, much research has focused on developing AR applications, which could be generally classified into two types, based upon the different devices used: optical see through AR and video see-through AR. Optical see-though AR uses a semi-transparent screen onto which computer generated objects can be projected; users, can simultaneously view the computer generated images and see through the screen to view the natural background environment and, thus, see an integrated AR scene. Video see-through AR uses cameras to capture the live scene as a video stream. For each viewed image frame, a captured video image frame is processed and computer generated virtual objects are added. One advantage of video see-through AR is that the mixed scene can then be displayed on different devices. With video see-through AR, markers and computer vision methods are often used for tracking.
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