Image Segmentation and Vector Matching for Styling Recommendations
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Solution Overview
Problem
Existing product recommendation systems in online shopping rely heavily on transaction data, which is often insufficient, especially for rapidly changing trends in fashion and home décor, leading to inaccurate and irrelevant recommendations.
Innovation Solution
An intelligent styling system that segments images from public sources using machine learning, generates numerical vector representations, and identifies similar images to create a recommendation catalog for complementary products.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If product recommendation systems rely on transaction data to learn co-occurrence patterns, then recommendations can be generated, but the recommendations become inaccurate and irrelevant when trends change rapidly
Solution Approach 1:
The patent replaces the traditional transaction-data-driven recommendation system with a visual-based system that uses image segmentation and vectorization to identify style trends from public sources. This substitution allows the system to respond to current fashion trends without being constrained by historical transaction data, eliminating the time lag and improving recommendation accuracy for rapidly changing trends.
Solution Approach 2:
The patent introduces visual data from public sources (such as social media images) as an intermediary to bridge the gap between current fashion trends and product recommendations. By segmenting and analyzing these visual images, the system can extract style information and generate recommendations that reflect current trends rather than relying solely on past transaction patterns.
2Adaptability or versatility
If the system uses visual data from public sources to identify style trends, then recommendations reflect current trends, but the system complexity increases
Solution Approach 1:
The patent applies image segmentation to divide complex visual data from public sources into manageable segments. By segmenting images into relevant portions and extracting specific visual features, the system can process and analyze style trends more efficiently, reducing the computational complexity while maintaining the ability to reflect current trends accurately.
Solution Approach 2:
The patent extracts key visual features and style information from public source images, separating the essential trend data from the surrounding visual noise. This extraction process simplifies the data representation and reduces the complexity of processing while preserving the adaptability to current fashion trends.
Data Source
AI summary
Systems and methods are provided for segmenting each image of a first plurality of images, using an image processing segmentation technique, into one or more category of a plurality of predefined categories to generate a set of image segments for the image. A numerical vector representation is generated for each image segment and for each image in a second plurality of images and used to determine a similarity between image segments and images in the second plurality of images. Each image segment in each set of image segment are replaced with an image in the second plurality of images that is similar to the image segment to generate a recommendation catalog comprising a plurality of sets of recommendation images.