Author : T S Prabhakar 1
Date of Publication :7th October 2022
Abstract: The concept of a virtual fitting room in real time has been proposed. The interest in online shopping has grown exponentially. When it comes to buying products like shirts that always require knowledge of how the clothes will fit when worn. This is the main reason why so few clothes are being bought online. As a result, a virtual dressing room that tells consumers how clothes fit personally will be a huge asset to online sellers that can give consumers a wide choice. For online marketers, this would be a great way to grow your market. The proposed system consists of a number of tasks, including locating the user's shirt and specifying the color of the user's shirt. In our proposed system we have used Alpha Channel Masking to mask the user's shirt, and libraries such as Numpy, OpenCV. Finally, we conclude that the concept of virtual fitting rooms that we have implemented helps humans in many ways, such as making their purchases easier, saving them time
Reference :
-
- Srinivasan K, Vivek S. “Implementation Of Virtual Fitting Room Using Image Processing”. IEEE International Conference on Computer, Communication and Signal Processing (ICCCSP- 2017).[1] [2] Aladdin Masri, Muhannad Al-Jabi. “Virtual Dressing Room Application”. 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT).
- HYUNWOO HWANGBO 1 , EUN HIE KIM2 , AND YOUNG JAE JANG 4 , (Member, IEEE).”Effects of 3D Virtual „„Try-On‟‟ on Online Sales and Customers‟ Purchasing Experiences”. Received July 4, 2020, accepted August 14, 2020, date of publication September 9, 2020, date of current version October 28, 2020
- Antitza Dantcheva, Francois Bremond, Piotr Bilinski.” Show me your face and I will tell you your height, weight and body mass index”.2018 24th International Conference on Pattern Recognition (ICPR) Beijing, China, August 20-24, 2018.[4]
- Chia-Wei Hsieh, Chieh-Yun Chen, Chien-Lung Chou, Hong-Han Shuai, Wen-Huang Cheng.” FITME: IMAGE-BASED VIRTUAL TRY-ON WITH ARBITRARY POSES”. 978-1-5386-6249- 6/19/$31.00 ©2019 IEEE
- uan Chang, Tao Peng∗ , Ruhan He, Xinrong Hu, Junping Liu, Zili Zhang, Minghua Jiang.” DPVTON: TOWARD DETAIL-PRESERVING IMAGE-BASED VIRTUAL TRY-ON NETWORK”. Authorized licensed use limited to: IEE EXplore.Downloaded on May 25,2021 at 02:41:08 UTC from IEEE Xplore
- Hemang M Shah. Aadhithya Dinesh, T Sree Sharmila.” Analysis of Facial Landmark Features to determine the best subset for finding Face Orientation”. Second International Conference on Computational Intelligence in Data Science (ICCIDS-2019).
- THAI THANH TUAN, MATIUR RAHMAN MINAR 1 , HEEJUNE AHN 1 , AND JOHN WAINWRIGHT 2.” Multiple Pose Virtual Try-On Based on 3D Clothing Reconstruction”. ReceivedJuly 15, 2021, accepted July 28, 2021, date of publication August 12, 2021, date of current version August 23, 2021
- Alexander Abdulov. Alexander Abramenkov.” Is Face 3D or 2D on Stereo Images?”. 2019 International Russian Automation Conference (RusAutoCon).
- Guha Balakrishnan, Amy ZhaoAdrian V. Dalca, Fredo Durand.” Synthesizing Images of Humans in Unseen Poses [cs.CV] 20 Apr 2018.[10]