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Virtual Trial Room Research Paper Summary
1.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 542 Development of Virtual Trial Rooms for Showrooms Harshitha HS1, Vaishnavi Kini2, Mrs. Mona3 Information science & Engineering BNM Institute of Technology, Bengaluru Karnataka, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Everyone loves to buy clothes, except for the hassle of rehearsal spaces. Augmented reality fashion displays seek to streamline the shopping process by eliminating all the hassle of tryingmultiplegarmentsintight, narrow trail spaces. You can identify people and view clothing and accessories such as watches in real time. This saves you the trouble of waiting in line and trying on clothes that someone might have worn before in the same rehearsal room. Applications of this technology can extend far beyond the realm of fashion stores to the realm of fashion design itself. This allows fashion designers to model prototype designs and early concept art and virtually test materials and resources before committing to physical representation of those designs. Key Words : OpenCV , Capturing ImageRGBNormalization, Face Detection, Haar Cascade Classifier 1. INTRODUCTION Despite increasing access to technology, people in the modern world are always busy. But for many, paying attention to appearance remains a top priority.Manypeople continue to spend time maintaining and expanding their wardrobes, buying special outfits, and more. In some cases, investing time involves going to a retail store to try on and buy clothing and accessories. The process of trying on some candidate garments and choosing the right size garmentcan be very time consuming. Online shopping offers a faster alternative thantraditional physical stores.However,despite its advantages, online shopping has some drawbacks.One of the disadvantages is that it can be difficult to imagine what a particular item would look like if worn by that person. This is because the size and shape of the body, hair and skin color of one person are very different. Over the last decade, simulations of trying on clothes have attracted the attention of many researchers. Much of this research used a multi- view system for fabric tracking and retexturing. Optical flow is widely used in today's apparel tracing and retexturing. 2. RELATED WORK A considerable lot of the current frameworks have variable discernments in the space of Augmented Realitywhichmade conceivable the execution of Trial Room idea virtual. Hardly any such E-Commerce locales like Lenskart, Abof, Snapchats and so forth, have created applications in light of augmented reality. One of those thoughtsis the Virtual TrialRoomwhich shows the client in wanted clothing. However, none of the ongoingapplicationsgivethethreelayeredpowerfulimaging. To develop this region weare proposing another framework called the "3D Virtual Trial Room". In the proposed framework, we will portray a basic and proficient Trial Room with virtual use. This application assists the client with imagining his/her own clothing without really wearing it. At first the client needs to confront the camera which centers the client picture and fit different ensembles to it and presentations.Thisessentiallyassiststhe client with knowing his/her decision effectively and give more noteworthy degree of fulfillment. As per the papers[1], [2] and [6] which are proposed by Shreya Kamani, F. Isikdogan and Vipin Paulindividually,theexecutionofvirtual preliminary room applicationisproposedwiththeutilization of a sensor known as Kinect sensor which essentially takes the bone estimation of an individual which is a method for deciding the size of client's body on which the virtual fabric must be expanded. In paper [3] which is proposed by Cecilia Garcia Martin, an android application is coordinated with the idea of expanded reality. There the proposed innovation is enlarging the virtual materials on a clients' static pictureandtheentireapplicationisunloadedin an android telephone. The applicationVirtualTrialRoomcan be pictured in fluctuated viewpoints and can be executed utilizing different equipment - programming combinations. One such is the utilization of OpenCV for this application advancement. This thought has been proposed in [4] and [5] by creators Nikki Singh and Sourabh Botre separately.
2.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 543 3. METHODOLOGY 3.1 System Architecture In this above figure shows the overall work flow of the project. We are passing live captured frame only as input system will detect the person human body and cloth pattern and matches the simulation. 4. IMPLEMENTATION 4.1 OpenCV Our essential thought is to distinguish the form of an individual's picture remaining before the camera. OpenCV is a cross stageopen-sourceprogrammingbundlethatcontains countless programming capabilities that give the client a door to interface with PC vision. The capabilitiesareworked to give a typical stage as well as framework for applications and issues connected with PC vision. The capabilities are coded so that they are proficient to incorporate AI thoughts and functionalities. OpenCV capabilities contains north of 2500 calculations that together give functionalities like face recognition, distinguishing objects, identifyhumanactivities in a video and considerably more. 4.2 Capturing Image OpenCV contains capabilities that are explicitly worked to catch pictures and video from a machine outfitted with various cameras, be it ht e inside or a remotely joined camera. It can peruse live video feed from a camera and separate it into outlines for helpful handling in additional stages. In this work we catch a video contribution of the client from the camera and apply the application code rationale straightforwardly on the information stream of casings without saving the real video record anyplace in the framework. This makes the application memory effective as video records are exceptionally enormous in size and need gpu resorces to deliver the video. Likewise by this training we can recreate a virtual climate whereinwetrulydoproper increases on the constant video picture of the client. 4.3 RGB Normalization OpenCV utilizes variety contrast based separation of items by distinguishing the pixels which dwell on the limits where varieties change esteems altogether, yet this cycle can't be completely precise as in true situations pictures can be hard to examine in light of variety separation. As an illustration consider the beneath image(include picture with fig no.) in which an individual's video feed is being broke down for identifying the T-Shirt he is wearing. 4.4 Haar Cascade Classifier Here we will work with face identification. At first, the calculation needs a great deal of positive pictures (pictures of countenances) and negative pictures (pictures without faces) to prepare the classifier. Then we really want to remove highlights from it. For this, haar highlightsdisplayed in beneath picture are utilized. They are very much like our convolutional piece. Each element is a solitary worth got by deducting amount of pixels under white square shape from amount of pixels under dark square shape.
3.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 544 OpenCV contains capabilities that are explicitly worked to catch pictures and video from a machine outfitted with various cameras. It can peruse live video feed from a camera and separate it into outlines for helpful handling in additional stages. In this work we catch a video contribution of the client from the camera and apply the application code rationale straightforwardly on the information stream of casings without saving the real video record anyplace in the framework. This makes the application memory effective as video records are exceptionally enormous in size and need gpu assets to deliver the video. Likewise by this training we can recreate a virtual climate wherein we truly do proper increases on the constant video picture of the client. 4. RESULTS & FUTURE WORK Fig - 1: Displaying selected product and to add to cart for trial Fig – 2: Output Screen displaying results Fig - 3: Accessories display screen Fig – 4 : Accessories try out 5. CONCLUSION As the last result, framework will show the accessible dresses from information base as per situating and estimations of client. The client can get to the GUI by hand motion and can choose the clothing or additionally select different classification. Accordingly it will be exceptionally helpful and bother free for the client to pick the ideal attire through virtual means without a lot of burden. As we have taken Front Haar Cascade calculation , here we have accepted face as the central issue and attempted to change the dresses and embellishments. Alongside this the cost of the item portrayal about the chose class can likewise be shown. REFERENCES [1] Shreya Kamani, Neel Vasa, Kriti Srivastava, "Virtual preliminary room utilizing increased reality", International Journal of Advanced Computer Technology(IJACT),Vol.3/6, Dec. 2014, pp. 98-102. [2] F. Isikdogan and G. Kara, "A Real Time Virtual Dressing Room Application utilizing Kinect", Cmpe537 Computer Vision Course Project, Bogazici University, January2012 [3] Cecilia Garcia Martin, Erdal Oruklu, "Human Friendly Interface Design for Virtual Fitting Room Applications on
4.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 09 Issue: 07 | July 2022 www.irjet.net p-ISSN: 2395-0072 © 2022, IRJET | Impact Factor value: 7.529 | ISO 9001:2008 Certified Journal | Page 545 Android Based Mobile Devices", Journal of Signal and Information Processing, Vol. 3/4, 2012, pp. 481-490. [4] Nikki Singh, Sagar Murade, Prem Lone, Vikas Mulaje "Virtual Trial Room" Vishwakarma Journal of Engineering Research ,Volume 1 Issue 4, December 2017 [5] Saurabh Botre, Sushant Chaudhari, Shamla Mantri, "Virtual Trial Room", International Journal of Computer Science Trends and Technology (IJCST), Volume 2 Issue 2, Mar-Apr 2014 [6] Vipin Paul, Sanju Abel J., Sudharsan S., Praveen M"VIRTUAL TRAIL ROOM", South Asian Journal of Engineering and Technology Vol.3, No.5 (2017), pp. 87-96 [7] Jamal Dargham, Ali Chekima, "Lips Detection in the Normalized RGB Color Scheme", Information and Communication Technologies, ICTTA'06.second,Volume:1, 2006.
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