Image Background Replacement Using Location and Lighting Matching
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Solution Overview
Problem
Users face challenges in replacing the background of images with visually appealing alternatives, as they often lack information about the geographic location of the original image and struggle to find suitable replacement images that match the original's parameters, leading to undesirable appearances.
Innovation Solution
The system uses image-processing algorithms to identify the object and background of an image, determine the geographic location, and retrieve images from the same location, selecting one based on matching parameters such as size, orientation, aspect ratio, and lighting conditions to generate a new image with a realistic appearance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If users manually search for replacement images without location information, then they can find images, but the process is time-consuming and the results may not match the original image's parameters
Solution Approach 1:
The system performs preliminary actions by automatically extracting location data and image parameters before the user needs to find a replacement image. It pre-processes the original image to identify geographic location, lighting conditions, time of day, and other parameters, so that when a replacement image is needed, the system already has the information required for accurate matching, eliminating manual search time while ensuring parameter compatibility.
Solution Approach 2:
The system introduces an intermediary database or service that stores geographic location data and image parameter information. This intermediary component mediates between the user's original image and the replacement image by providing a structured way to match parameters such as location, lighting, time of day, and camera settings, thereby ensuring accurate matches without manual searching.
2Ease of operation
If users replace background without matching parameters, then the process is simple, but the resulting image has undesirable appearance
Solution Approach 1:
The system performs self-service by automatically analyzing the original image to extract all necessary parameters including geographic location, lighting conditions, time of day, and camera settings. It then uses these extracted parameters to automatically select and match with appropriate replacement images, eliminating the need for users to manually adjust or specify matching criteria while ensuring high visual quality through automated parameter-based selection.
Solution Approach 2:
The system changes parameters by automatically extracting and comparing multiple image parameters such as lighting conditions, time of day, geographic location, and camera settings. It uses these parameter changes and comparisons to filter and select replacement images that match the original image's characteristics, thereby maintaining visual quality and realism without requiring manual user intervention in the parameter matching process.
3Reliability
If the system extracts and matches multiple image parameters, then the visual quality improves, but the computational complexity increases
Solution Approach 1:
The system applies segmentation by dividing the complex task of parameter extraction and image matching into separate modular components. It segments the process into: (1) extracting specific parameters from the original image (location, lighting, time, camera settings), (2) storing these parameters in a structured database, and (3) matching replacement images based on these segmented parameters. This segmentation reduces computational complexity by handling each parameter independently rather than processing all parameters simultaneously as a single complex task.
Data Source
AI summary
Systems and methods are described for replacing a background portion of an image. An illustrative method includes receiving a first image, identifying a background portion of the first image and a subject portion of the first image, identifying a geographic location corresponding to the background portion of the first image, retrieving a plurality of other images depicting the geographic location, selecting a second image from the plurality of other images, wherein the second image is associated with metadata indicating that the second image was captured during a predetermined time period, and generating for display a third image comprising the subject portion of the first image placed over the second image.