Composite Image Generation for Apparel Fit Visualization
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Solution Overview
Problem
Consumers lack confidence in buying apparel online due to the lack of size standardization and fit variability, as well as the inability to try on garments before purchasing, leading to higher return rates and abandoned purchases.
Innovation Solution
A system that generates composite images by augmenting graphical representations of products into representative images of consumers, allowing them to see how the products fit and hang, using image processing and machine learning models to select appropriate images based on product profiles and consumer data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If consumers purchase apparel online without trying on garments, then purchasing convenience is improved, but purchase confidence deteriorates
Solution Approach 1:
The system creates virtual copies of garments and consumers through graphical representations. Garment graphical representations are generated from product images, and consumer graphical representations are extracted from uploaded photos. These copies are then combined in composite images to simulate the garment worn on the consumer, allowing online shoppers to visualize fit without physical try-on sessions.
Solution Approach 2:
The composite image generation system acts as an intermediary between the consumer and the garment. Instead of directly trying on the physical garment, the consumer interacts with a virtual representation through the composite image, which mediates the evaluation of fit and appearance, bridging the gap between online shopping and physical try-on experiences.
2Ease of operation
If consumers cannot see how garments fit before purchasing, then online shopping simplicity is improved, but return rates increase
Solution Approach 1:
The system performs preliminary visualization of garment fit before the consumer makes a purchasing decision. By generating composite images that show how the garment will look on the consumer's body, the system allows consumers to evaluate fit and appearance in advance, preventing mismatches and reducing the likelihood of returns.
Solution Approach 2:
Virtual copies of the garment are superimposed onto consumer images to create realistic representations of fit. This copying approach allows consumers to see the garment on their body type without the garment physically existing on them, providing accurate fit information before purchase.
3Adaptability or versatility
If garment fit varies from garment to garment, then apparel diversity is improved, but size standardization deteriorates
Solution Approach 1:
The system applies local quality analysis by examining specific regions of the consumer's body where garments fit. The composite images allow consumers to see how garments fit in critical areas such as shoulders, waist, and hips, providing localized fit information that accounts for variations in garment construction and body shape, rather than relying on universal size standards.
4Ease of operation
If consumers lack opportunity to try on garments, then online shopping accessibility is improved, but fit assessment capability deteriorates
Solution Approach 1:
The system creates visual copies of the garment-on-consumer scenario through composite images. By merging the garment graphical representation with the consumer graphical representation, the system provides a visual measurement of fit that compensates for the lack of physical try-on, allowing consumers to assess fit accuracy remotely.
Solution Approach 2:
The system replaces the mechanical action of physically trying on garments with a digital image processing system. Instead of the consumer manually putting on and removing garments to assess fit, the system automatically generates composite images that show the fit, substituting physical interaction with computational image manipulation.
Data Source
AI summary
Accessing images associated with users for generating composite images and/or making product recommendations based at least partly on the images to enhance online shopping experiences is described. A service provider can access images associated with a user and identify a product of interest to the user. The service provider can determine a fitness score for an image of the images, the fitness score indicating an appropriateness of the image for presenting the product of interest via a device associated with the user, and select the image as a representative image based at least in part on the fitness score. The service provider can generate, from the representative image, a composite image that visually depicts a graphical representation of the product of interest and cause the composite image to be presented to the user via the device.