Virtual Try-On Image Harmonization for Pose and Lighting Matching
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Solution Overview
Problem
Existing virtual try-on technologies struggle to generate a natural and high-quality image of a user trying on clothes, often resulting in unrealistic or mismatched appearances due to variations in lighting and pose estimation inaccuracies.
Innovation Solution
A system and method that utilizes a camera and display device connected by a processor, employing neural networks for pose estimation and image harmonization to synthesize clothes with a user object, adjusting for lighting and pose matching, and further harmonizing with background images to create a realistic virtual try-on image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing virtual try-on technologies are used to generate images, then the process is simple, but the image quality is unrealistic and mismatched due to lighting variations and pose estimation inaccuracies
Solution Approach 1:
The system segments the virtual try-on process into distinct modules: pose estimation module that analyzes user posture, image harmonization module that adjusts lighting and color, and synthesis module that combines clothes with user image. This segmentation allows each module to specialize in improving specific aspects of image quality while maintaining manageable system complexity.
Solution Approach 2:
The system performs preliminary pose estimation and lighting analysis before synthesizing the final try-on image. By pre-processing the user image to estimate pose parameters and characterize lighting conditions, the system prepares optimized input data for the synthesis module, thereby improving final image quality without proportionally increasing overall complexity.
2Measurement precision
If pose estimation is performed to match user posture with clothes, then the try-on accuracy is improved, but the processing time and computational complexity increase
Solution Approach 1:
The pose estimation module focuses on estimating only the critical keypoints necessary for clothes fitting (such as shoulder, waist, and hip positions) rather than performing complete body pose analysis. This partial action approach achieves sufficient accuracy for virtual try-on while significantly reducing computational time and complexity.
Solution Approach 2:
The system uses pre-trained pose estimation models that have been copied from existing research frameworks, allowing rapid inference without requiring extensive retraining. This enables accurate pose estimation to be performed efficiently on user images during the virtual try-on process.
3Manufacturing precision
If image harmonization is applied to match lighting and colors, then the natural appearance is improved, but the computational resources and processing time increase
Solution Approach 1:
The image harmonization module performs preliminary analysis of lighting conditions in the user image before synthesizing the final result. By pre-characterizing the lighting environment and pre-adjusting color parameters, the system reduces the computational burden during the final synthesis stage, thereby improving energy efficiency while maintaining high lighting and color matching quality.
4Manufacturing precision
If multiple processing steps are used to enhance realism, then the visual quality is improved, but the device complexity and operation difficulty increase
Solution Approach 1:
The virtual try-on system automatically performs pose estimation, image harmonization, and synthesis without requiring user intervention for each processing step. The system self-adjusts parameters based on the uploaded user image and selected clothes, thereby achieving high visual realism while maintaining ease of operation through full automation.
Data Source
AI summary
A computer device for providing a virtual try-on image includes a camera interface connected to a camera, a display interface connected to a display device, and a processor configured to communicate with the camera through the camera interface and communicate with the display device through the display interface. The processor is configured to receive input images generated by the camera photographing a user through the camera interface, by processing a user object obtained from one of the input images, generate pose estimation data representing a pose of the user object, select an input image having the user object of which pose represented by the pose estimation data matches a reference pose, generate the virtual try-on image by synthesizing a clothes object with the user object included in the selected input image, and visualize the virtual try-on image by controlling the display device through the display interface.