AI Clothing Coordination Recommendation via Harmony and TPO Scoring
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Solution Overview
Problem
Existing clothing processing technologies cannot collect user-owned clothing information, preventing them from recommending suitable clothing coordination based on the user's actual garments, time, place, and occasion.
Innovation Solution
A method and apparatus that collect clothing information from home appliances and user terminals, classify style information using deep neural networks, calculate harmony and TPO matching scores, and recommend coordination information based on user requests, incorporating weather information and intended purchases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing clothing processing technologies are used, then basic clothing processing functions are provided, but user-owned clothing information cannot be collected for personalized recommendations
Solution Approach 1:
The clothing processing apparatus is enhanced with multiple functions beyond basic processing, including image capture of user's clothing, style classification using deep neural networks, harmony score calculation, and personalized recommendation generation. This multi-functionality enables the system to collect and utilize user clothing information for adaptive recommendations.
Solution Approach 2:
A communication unit serves as an intermediary to collect clothing information from various sources including the user's terminal device and the clothing processing apparatus itself. This intermediary component enables data gathering from multiple channels to build a comprehensive user clothing database for personalized recommendations.
2Measurement precision
If comprehensive clothing information collection and analysis is implemented, then personalized recommendation accuracy is improved, but system complexity increases
Solution Approach 1:
The recommendation system is divided into distinct functional modules: an image capture unit for acquiring clothing images, a classification unit using deep neural networks for style recognition, a scoring unit for calculating harmony and TPO matching scores, and a recommendation unit for generating personalized suggestions. This segmentation allows each component to perform its specific function with high precision while maintaining manageable system complexity through modular architecture.
3Measurement precision
If deep neural network classification and multiple scoring calculations are performed, then style classification accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing clothing information, including capturing images of user's existing clothing, pre-classifying styles using deep neural networks, and pre-calculating harmony scores and TPO matching scores for various clothing combinations. This preliminary processing enables fast retrieval and recommendation generation when the user requests suggestions, significantly reducing real-time processing delays.
Data Source
AI summary
Disclosed are a method and an apparatus for recommending clothing coordination information in the 5G communication environment by executing an artificial intelligence (AI) algorithm and/or a machine learning algorithm, which have been mounted therein. A method for recommending clothing coordination information according to an embodiment of the present disclosure may include classifying style information through an analysis of a collected clothing image, calculating a harmony matching score between clothing images included in the classified style information or a TPO matching score on a time, a place, and an occasion of each of the clothing images and registering the calculated score in a database, recognizing a clothing coordination request speech voice received from a user, and confirming the speech intention of the clothing coordination request speech voice of the user, and recommending clothing coordination information corresponding to the speech intention, based on the harmony matching score or the TPO matching score.