Vehicle Imaging for Automated Clothing Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing clothing and accessories recommendation systems require users to manually capture and upload images of their clothing and accessories, which is time-consuming and burdensome, necessitating an improvement in user convenience.
Innovation Solution
An information processing system that includes a vehicle equipped with an imaging unit to capture images of users' clothing and accessories, which are then recognized and used to train a supervised learning model based on schedule and weather information, providing automated recommendations to a terminal device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually capture and upload images of their clothing and accessories, then the system can obtain accurate clothing data, but the operational burden and time consumption increase
Solution Approach 1:
The system enables self-service by automatically capturing clothing images through the vehicle's imaging devices and performing recognition processing without requiring user intervention. The vehicle's cameras automatically detect and capture images of clothing and accessories when the user enters, eliminating the need for manual photographing and uploading by the user.
Solution Approach 2:
The manual mechanical process of users taking photos and uploading images is replaced by an automated optical recognition system. The vehicle's imaging devices capture images, and the server performs automated clothing recognition and data extraction, substituting the manual operational sequence with an automated vision-based system.
2Loss of information
If users manually upload images to the server, then the system can process clothing information, but the time consumption and operational steps increase
Solution Approach 1:
The system performs preliminary action by capturing clothing images in advance when the user enters the vehicle, rather than waiting for the user to manually photograph and upload later. The imaging devices continuously capture images during the user's entry and movement into the vehicle, so the data collection is already completed before the user needs recommendations.
Solution Approach 2:
The useful action of data collection is made continuous through the vehicle's imaging devices that continuously capture images as the user enters and moves into the vehicle. This continuous capture ensures no clothing items are missed and eliminates the discontinuous manual process of taking separate photos of each item.
3Ease of operation
If the system uses automated image capture and recognition, then user convenience is improved, but the system complexity increases
Solution Approach 1:
The vehicle's imaging devices serve multiple functions: they capture images for clothing recognition, perform face authentication to identify the user, and support the supervised learning model training. This multi-functionality reduces the need for dedicated separate systems while maintaining the automated convenience benefits.
Solution Approach 2:
The server acts as an intermediary that handles the complex recognition and processing tasks, receiving images from the vehicle's simple imaging devices and returning processed clothing information. This intermediary architecture allows the vehicle to remain relatively simple while the server handles the computational complexity of clothing recognition and recommendation generation.
Data Source
AI summary
An information processing system includes: a vehicle configured to capture an image of clothing and accessories of a user when the user gets in the vehicle to generate a clothing and accessories image; and a server configured to communicate with the vehicle and a terminal device of the user. The server is configured to: train a supervised learning model by using at least one of schedule information of the user and weather information as input data and clothing and accessories information as training data; estimate clothing and accessories according to at least one of schedule information of the user and weather information for the next time the user gets in the vehicle by using the trained supervised learning model; and send clothing and accessories recommendation information indicating the estimated clothing and accessories to the terminal device of the user.