AI Clothing Collocation via Feature Vector Matching
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Solution Overview
Problem
Users face challenges in visualizing effective clothing collocations when purchasing online, as existing methods rely on preset combinations rather than personalized matching based on the target clothing's features.
Innovation Solution
A method and apparatus that perform feature extraction on target clothing images, match them with a preset clothing information set using feature vectors, and form collocation image groups based on attribute information and matching degrees, utilizing pre-trained neural networks and models for attribute prediction and matching degree calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If preset clothing combinations are used for collocation, then the system complexity is reduced and operation is simplified, but the collocation accuracy and personalization are insufficient
Solution Approach 1:
The system automatically performs feature extraction, attribute prediction, and matching operations without requiring user intervention. The server autonomously processes the target clothing image, extracts features, predicts attributes, matches with the clothing database, and generates collocation results, making the complex process transparent and simple for users while achieving high accuracy through automated AI processing
Solution Approach 2:
The patent replaces manual or rule-based collocation methods with automated image recognition and attribute prediction systems. By using deep learning models to automatically extract features and predict attributes from images, the system substitutes complex mechanical matching operations with intelligent automated processing, achieving both operational simplicity and high matching accuracy
2Measurement precision
If feature extraction and attribute prediction models are implemented, then collocation matching accuracy is improved, but the system complexity and computational requirements increase
Solution Approach 1:
The system performs feature extraction and attribute prediction in advance during the image processing stage. By pre-extracting features and pre-predicting attributes before the actual matching process, the complex computational work is completed upfront, enabling faster and simpler real-time matching operations while maintaining high accuracy
Solution Approach 2:
The patent introduces an intermediary layer of attribute prediction models that bridge the gap between raw image data and collocation matching. The model translates image features into structured attribute information (category, style, texture, color), which then serves as the basis for matching, simplifying the overall system architecture while improving matching precision
3Reliability
If multiple attribute predictions are performed on target clothing, then the collocation effectiveness is improved, but the processing time and computational resources increase
Solution Approach 1:
The system performs feature extraction and multiple attribute predictions (category, style, texture, color) in advance during the initial image processing phase. By completing all necessary attribute predictions before the matching process, the system ensures comprehensive and accurate collocation suggestions while the actual user interaction remains fast and efficient
Solution Approach 2:
The patent combines multiple attribute prediction tasks (category prediction, style prediction, texture prediction, color prediction) into a unified processing framework. By merging these predictions into a single integrated analysis of the target clothing image, the system achieves comprehensive collocation effectiveness without requiring separate sequential processing steps, thereby reducing overall processing time
Data Source
AI summary
Disclosed in embodiments of the present application are an information presentation method and device. One specific embodiment of a system comprises: receiving a collocation request for performing clothing collocation on target clothing, the collocation request comprising a target clothing image; performing feature extraction on the target clothing image to obtain a feature vector of the target clothing image; and selecting, from a preset clothing information set on the basis of the feature vector of the target clothing image, a clothing image having a feature vector matching the feature vector of the target clothing image to form at least one group of clothing collocation images together with the target clothing image, wherein the clothing information set comprises clothing images and feature vectors of the clothing images. The embodiment improves clothing collocation effects.