Complementary Image Collage Layout With Source-Linked Segments
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Solution Overview
Problem
Users face challenges in organizing and maintaining digital content, particularly with systems that allow for storing images and links to websites, as existing systems lack efficient methods for collaging and interacting with extracted image segments to facilitate further exploration and consumption.
Innovation Solution
A system and method for generating collages from extracted image segments, where metadata is maintained to link back to the origin, allowing interaction and purchase of objects, and utilizing machine learning to automatically generate collages based on initial image segments and complementary segments, with options for user interaction and customization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users store images and links in existing systems, then digital content can be maintained, but efficient organization and interaction with the content becomes difficult
Solution Approach 1:
The system divides digital content into discrete image segments that can be independently extracted, organized, and interacted with. Each segment maintains metadata links to original sources while presenting simplified visual elements for easy organization and manipulation.
Solution Approach 2:
The patent introduces an intermediary collage generation system that bridges raw digital content and user organization needs. This intermediary layer processes images into structured segments with metadata, enabling efficient organization without requiring users to directly manage complex source data.
2Adaptability or versatility
If the system allows manual collaging of image segments, then user customization is enabled, but time consumption increases
Solution Approach 1:
The system performs preliminary processing by automatically extracting image segments and generating preliminary collages before user interaction. Machine learning algorithms pre-organize segments based on visual similarity and contextual relationships, reducing the time users need to spend on manual arrangement while preserving customization capabilities.
Solution Approach 2:
The collage generation system provides self-service functionality where machine learning algorithms automatically determine complementary image segments and assemble collages without requiring extensive user input. Users can then make minor adjustments rather than creating collages from scratch, significantly reducing time investment.
3Productivity
If the system extracts and organizes image segments with metadata links, then content exploration is facilitated, but system complexity increases
Solution Approach 1:
The system extracts only the essential visual elements and their corresponding metadata links from the original content, separating the functional information needed for exploration from the full source data. This extraction creates a simplified representation that maintains exploration capabilities while reducing system complexity.
Solution Approach 2:
The metadata structure is designed to be universal, serving multiple functions including content identification, source linking, and exploration navigation. This multi-functional metadata approach consolidates what would otherwise require separate systems into a single integrated structure, reducing overall complexity.
Data Source
AI summary
Described are systems and methods of identifying complementary image segments and generating collages of the complementary image segments. Based on an initial image segment, the complementary image segments may first be determined. Then, a layout of the collage may be determined based on the initial image segment and the complementary image segments. The collage may then be generated using the initial image segment, the complementary image segments, and the layout. The origin information, such as the source image, source image location, etc., from which the extracted image segment is generated is maintained as metadata so that interaction with the extracted image segment on the collage can be used to determine and/or return to the origin of the extracted image segment. Collages may be updated, shared, adjusted, etc.