Journal article
In-home application (App) for 3D virtual garment fitting dressing room
Multimedia tools and applications, v 80(4), pp 5203-5224
01 Feb 2021
Abstract
This work introduces a novel method for the creation of an in-home virtual dressing room for garment fitting using an integrated system consisting of personalized 3D body model reconstruction and garment fitting simulation. Our method gives saliency to and establishes a relational interconnection between the massive scatter points on the 3D generic model. Starting with a small set of anthropometric interconnected ordered intrinsic control points residing on the silhouette of the projections of the generic model, corresponding control points on two canonical images of the person are automatically found - hence importing equivalent saliency between the two sets. Further equivalent saliencies between the projected points from the generic model and the canonical images are established through a loop subdivision process. Human shape mesh personalization is done through morphing the points on the generic model to follow and be consistent with their equivalent points on the canonical images. The 3D reconstruction yields sub resolution errors (high level accuracy) when compared to the average resolution of the original model using the CAESAR dataset. The reconstructed model is then fitted with garments sized to the 3D personalized model given at least one frontal image of the garment with no requirement for a full 3D view of the garment. Our method can also be applied to virtual fitting system for online stores and/or for clothing design and personalized garment simulation. The method is convenient, simple, efficient, and requires no intervention from the user aside from taking two images with a camera or smart phone.
Metrics
Details
- Title
- In-home application (App) for 3D virtual garment fitting dressing room
- Creators
- Chenxi Li - Drexel UniversityFernand Cohen - Drexel University
- Publication Details
- Multimedia tools and applications, v 80(4), pp 5203-5224
- Publisher
- Springer Nature
- Number of pages
- 22
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000574800100001
- Scopus ID
- 2-s2.0-85091947311
- Other Identifier
- 991019168583304721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Information Systems
- Computer Science, Software Engineering
- Computer Science, Theory & Methods
- Engineering, Electrical & Electronic