Automated Image Composition Generation System
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Solution Overview
Problem
Social network systems lack efficient methods to automatically generate high-quality image compositions from user-uploaded photos, such as action and clutter-free compositions, which require manual effort and user knowledge.
Innovation Solution
A system that receives photos from users, determines composition types, and generates action or clutter-free compositions by selecting, aligning, normalizing, smoothing, and blending photos based on predetermined criteria, using recognition algorithms to identify foreground and background objects and remove clutter, thereby creating visually appealing compositions without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual photo composition is used, then composition quality can be controlled, but user effort and time required increase
Solution Approach 1:
The system performs self-service by automatically analyzing uploaded photos, identifying composition types (action, clutter-free, etc.), and generating compositions without requiring user intervention. The system selects photos, aligns them, removes clutter, and creates final compositions autonomously based on predetermined criteria.
Solution Approach 2:
The system performs preliminary actions by pre-defining composition types and selection criteria before user input. It prepares templates and guidelines in advance that automatically guide the photo selection and composition process, eliminating the need for users to manually create compositions from scratch.
2Extent of automation
If automated composition generation is implemented, then user effort is reduced, but system complexity increases
Solution Approach 1:
The system segments the complex photo composition task into distinct manageable modules: photo upload reception, composition type determination, photo selection based on criteria, alignment processing, clutter removal, and final composition generation. Each module handles a specific aspect independently, making the overall complex system more manageable and maintainable.
Solution Approach 2:
The system implements multi-functionality by handling multiple composition types (action compositions, clutter-free compositions, etc.) within a single unified platform. The same system can generate different types of compositions from the same set of uploaded photos by applying different predetermined criteria, reducing the need for separate specialized systems.
3Adaptability or versatility
If multiple composition types are generated, then user options increase, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary determination of composition types and prepares corresponding predetermined criteria before actual composition generation. This pre-planning allows the system to efficiently process multiple composition types without redundant analysis, as the selection criteria and processing guidelines are already established based on the determined composition type.
Solution Approach 2:
The system applies partial action by generating only the necessary composition types based on the uploaded photos and predetermined criteria, rather than creating all possible composition variations. It selectively processes photos according to the determined composition type, avoiding unnecessary computational resources while still providing diverse composition options when appropriate.
Data Source
AI summary
Implementations generally relate to generating image compositions. In some implementations, a method includes receiving a plurality of photos from a user and determining one or more composition types from the photos. The method further includes generating one or more compositions from the received photos based on the one or more determined composition types, where each composition is based on modified foregrounds of the photos. The method further includes providing the one or more generated compositions to the user.