GENERATIVE APPAREL RECOMMENDATIONS USING IMAGES OF A PERSON

Smart overview of the Invention

The patent application outlines a system designed to provide generative apparel recommendations within a conversational platform. Utilizing a visual AI model, the system generates new images of a person wearing different apparel items or hairstyles based on an input image. These AI-generated images are analyzed to identify apparel patterns and components, which are then used to curate a set of personalized apparel recommendations. The curated items are displayed through a user interface, offering users tailored clothing suggestions.

Technical Field

This invention pertains to digital communication systems, specifically focusing on methods for delivering customized clothing recommendations through conversational interfaces. The technology leverages advancements in artificial intelligence to enhance the online shopping experience by providing personalized and visually appealing clothing options.

Background

The rise of digital communication tools has transformed how individuals shop online, yet finding personalized clothing remains challenging. Conventional platforms often fail to offer tailored suggestions that match an individual's style and wardrobe. Current AI-driven solutions typically rely on explicit user inputs and predetermined algorithms, lacking the ability to provide comprehensive recommendations that consider users' existing attire.

Innovation

The proposed system addresses these limitations by integrating generative AI with conversational interfaces. Users upload photos depicting their current wardrobe, which are processed by a visual AI model to extract clothing patterns and components. A conversational AI model engages with users to determine their preferences, curating a set of clothing items based on these interactions. The system continuously refines its recommendations based on user feedback and ongoing conversations.

Implementation

In practice, the system captures user photos and applies AI models to identify clothing patterns. Through interactive dialogues, it refines user preferences and generates virtual clothing items that overlay on existing photos. These virtual items are matched with inventory items for purchase suggestions. The system evolves over time, adapting its recommendations through continuous learning from user interactions.