Virtual Apparel Texture Replacement Preserving Wrinkles
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Solution Overview
Problem
Conventional virtual trying technologies for apparel do not effectively account for texture, color, folds, and wrinkles, leading to inefficient and potentially damaging physical trials in garment showrooms, and lack realism in virtual representations.
Innovation Solution
A method and system for virtual apparel trials that utilize near-real-time video processing to calculate and refine histograms, localize the apparel region, capture light intensity variations, and replace textures in a video file, ensuring accurate and realistic virtual fitting by comparing and updating histograms across frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional virtual trying technologies are used, then the process is simplified, but texture, color, folds and wrinkles are not effectively preserved
Solution Approach 1:
The patent segments the apparel into multiple overlapping subimages or image windows for independent histogram calculation and analysis. This allows detailed local texture and wrinkle analysis while managing computational complexity through divide-and-conquer approach.
Solution Approach 2:
The patent transitions from analyzing single image frames to processing video sequences with temporal dimension. By calculating histograms across multiple frames and updating reference histograms dynamically, the system captures wrinkles and folds that appear during movement, enhancing texture preservation.
2Measurement precision
If physical trials are conducted to ensure accurate fitting, then fitting accuracy is improved, but time consumption and damage risk increase
Solution Approach 1:
The patent creates a virtual copy of the apparel by replacing the original texture with a target apparel texture while preserving the detected wrinkle patterns and light intensity variations. This virtual copy provides accurate fitting information without requiring physical trial.
Solution Approach 2:
The patent replaces the mechanical physical trial process with an automated computer vision system that uses video processing, histogram analysis, and image synthesis to determine fitting accuracy, eliminating the need for physical garment handling.
3Measurement precision
If physical trials are conducted to ensure accurate fitting, then fitting accuracy is improved, but damage risk to apparels increases
Solution Approach 1:
The patent creates a virtual representation of the fitting process by synthesizing images that combine the detected body shape and wrinkle patterns with the target apparel texture. This eliminates direct contact with the physical garment, preventing damage while maintaining fitting accuracy.
Solution Approach 2:
The patent introduces an intermediary computer vision system that captures fitting information through video processing and histogram analysis without requiring physical interaction between the buyer and the apparel, thus preventing damage.
4Measurement precision
If histogram correlation and thresholding are applied for apparel region capture, then localization accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent divides the apparel region into multiple overlapping subimages or image windows, calculating histograms for each segment independently. This segmentation approach improves localization accuracy by capturing local variations while distributing computational load across multiple smaller processing units.
Solution Approach 2:
The patent calculates histograms for multiple overlapping subimages rather than a single global histogram. This excessive sampling ensures comprehensive coverage of the apparel region and improves localization accuracy, with the trade-off managed through efficient processing of redundant overlapping regions.
5Measurement precision
If light intensity variation is used to capture wrinkles and folds, then wrinkle detection accuracy is improved, but sensitivity to lighting conditions increases
Solution Approach 1:
The patent extends wrinkle detection from static single-frame analysis to dynamic video sequence analysis. By tracking light intensity variations across multiple frames and updating reference histograms, the system can distinguish true wrinkle patterns from transient lighting effects, improving both accuracy and lighting adaptability.
Solution Approach 2:
The patent uses feedback from multiple video frames to refine wrinkle detection. By comparing light intensity patterns across frames and updating the reference histogram, the system can distinguish consistent wrinkle features from variable lighting conditions, improving robustness.
Data Source
AI summary
The present disclosure provides virtual replacement of the texture of an apparel with a different texture, also taking care of the wrinkles, body shape etc. The apparel worn by the user is identified/localized in all the frames of a video file, and replaced with a pre-identified texture from the catalogue. Multiple histograms are calculated to localize the region of the apparel using Correlation coefficient. The variation in light intensity is used to capture the wrinkles and folds etc on the apparel.