Sizing Content Recommendation System Using Image Analysis
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Solution Overview
Problem
The process of determining items that match a buyer's size in online marketplaces is often time-consuming and inaccurate due to the lack of efficient sizing data collection and matching mechanisms.
Innovation Solution
A sizing content recommendation system that determines user sizing data through image analysis using a standard-sized marker, allowing for the identification of matching items in online marketplaces, and prioritizes results based on user preferences and past interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual sizing methods are used, then users can find size-specific items, but the process is time-consuming and inaccurate
Solution Approach 1:
The patent replaces manual sizing measurement methods with image processing technology. The system captures images of users and automatically determines their body dimensions through computer vision algorithms, eliminating the need for manual measurement while improving both accuracy and speed of sizing determination.
Solution Approach 2:
The system enables users to automatically obtain their sizing information through self-captured images. Users take photos of themselves using their devices, and the system automatically processes these images to extract sizing data without requiring user input or manual measurement, making the process both rapid and accurate.
2Reliability
If comprehensive sizing data collection is implemented, then matching accuracy improves, but system complexity increases
Solution Approach 1:
The patent makes the image processing system multi-functional by using a single image capture mechanism to extract multiple sizing parameters simultaneously. The same image processing algorithms determine various body dimensions (height, waist, hips, etc.) from one image, eliminating the need for separate measurement devices for each parameter and reducing overall system complexity.
Solution Approach 2:
The system introduces an image as an intermediary medium between the user and the sizing data. Instead of directly measuring users with multiple specialized devices, the system uses images as a universal intermediary that can be captured by common devices (smartphones, cameras) and then processed to extract comprehensive sizing information, simplifying the data collection infrastructure.
3Extent of automation
If image-based sizing is used, then sizing determination becomes automated and accurate, but computing resources increase
Solution Approach 1:
The system applies partial action by processing only the essential features needed for sizing determination from images, rather than performing exhaustive analysis. The image processing algorithms focus specifically on extracting body dimension information relevant to clothing sizing, avoiding unnecessary computational overhead while maintaining automation and accuracy.
Solution Approach 2:
The system performs preliminary action by pre-processing and storing sizing data in structured formats during image analysis. By organizing sizing information in advance with proper metadata and relationships, the system reduces the computational burden during subsequent item matching operations, as the sizing data is already prepared and indexed for efficient comparison.
Data Source
AI summary
In various example embodiments, systems and methods to provide content recommendations are provided. Search parameters are received from a user. An attribute associated with the user is derived. Using the search parameters and the attribute, content from a database that is within a predetermined margin of difference of the derived attribute are determined. A list of the content is caused to be presented in a user interface of the user.