Seamless Image Personalization With Metadata-Based Region Inpainting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image editing systems require significant computational resources and time to seamlessly integrate replacement individuals into reference images, especially when multiple individuals are involved, often leading to inefficiencies and inaccuracies in preserving spatial relationships and anatomical correctness.
Innovation Solution
A system that utilizes metadata comparison and machine learning models to identify specific portions of an image for inpainting, leveraging the geometry of the reference image to preserve spatial relationships and employing a template image database for iterative personalization, reducing computational load by selectively processing directed portions of the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing image editing systems process entire reference images to integrate replacement individuals, then integration accuracy is improved, but computational resources and processing time increase significantly
Solution Approach 1:
The patent segments the reference image into multiple regions based on metadata comparison between reference and replacement individuals. The system identifies specific regions where replacement is needed and processes only those segments rather than the entire image, thereby maintaining integration accuracy while significantly reducing computational resources and processing time.
Solution Approach 2:
The patent applies local quality by directing computational resources to specific regions of the image where replacement individuals need to be integrated. By using metadata comparison to identify relevant regions and applying inpainting only to those areas, the system achieves high integration accuracy in critical areas without the need to process the entire image at full resolution.
2Manufacturing precision
If existing image editing systems process entire reference images to preserve spatial relationships, then anatomical correctness is improved, but computational load increases
Solution Approach 1:
The patent divides the image processing task into segments by identifying specific regions containing reference individuals through metadata comparison. By processing only these segmented regions rather than the entire image, the system maintains anatomical correctness in the areas that matter while dramatically reducing overall computational load.
Solution Approach 2:
The patent applies partial action by processing only the portions of the image that contain reference individuals needing replacement. Rather than applying excessive computational resources to process the entire image, the system performs targeted processing on relevant regions, achieving sufficient anatomical correctness without unnecessary computational overhead.
3Manufacturing precision
If existing image editing systems perform comprehensive image processing, then integration seamlessness is improved, but processing time increases
Solution Approach 1:
The patent segments the processing task by using metadata comparison to identify specific regions containing reference individuals. By applying inpainting and integration techniques only to these identified segments rather than the entire image, the system achieves seamless integration in critical areas while reducing overall processing time significantly.
Solution Approach 2:
The patent performs preliminary action by using metadata comparison to pre-identify regions containing reference individuals before initiating the computationally intensive inpainting process. This preliminary identification step allows the system to focus subsequent processing only on relevant areas, ensuring seamless integration where needed while minimizing total processing time.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an inpainted image of a replacement individual in the place of a reference individual in a reference image using a metadata comparison. In one aspect, a system comprises receiving a first image comprising one or more reference individuals and a second image comprising one or more replacement individuals; obtaining replacement metadata and reference metadata; determining, based on the obtained replacement metadata and reference metadata, at least one portion of the first image for replacing corresponding with the one or more reference individuals; and generating a third image that comprises a modification of the first image wherein the at least one portion of the first image is replaced with replacement content, the replacement content being generated based on (i) the one or more replacement individuals, (ii) the replacement metadata, and (iii) the reference metadata.