Image Layout Arrangement Using Source-Specific Evaluation
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Solution Overview
Problem
Existing automatic image layout processing methods fail to effectively differentiate between still and moving image data, leading to suboptimal layout generation as they do not consider the source of image acquisition, such as digital cameras or social networking services.
Innovation Solution
An image processing apparatus and method that analyzes both still and moving image data, incorporating features like motion analysis, object detection, and scene classification to assign scores and select images for layout based on their content and acquisition source, ensuring higher user satisfaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If automatic layout processing is performed without considering image data source, then the processing is simple and fast, but the layout quality and user satisfaction are reduced
Solution Approach 1:
The patent segments image data into distinct categories based on acquisition source (still images from digital cameras versus moving images from social networking services). This segmentation allows the system to apply different evaluation criteria and scoring methods to each category, thereby improving layout quality while managing complexity through structured organization of the processing logic.
Solution Approach 2:
The patent applies local quality by treating different image data sources with different evaluation characteristics. Still images are evaluated based on one set of criteria (e.g., photo quality, composition), while moving images are evaluated based on another set of criteria (e.g., motion content, engagement). This differentiated approach optimizes layout quality for each image type without requiring complete redesign of the entire processing system.
2Reliability
If image evaluation does not differentiate between still and moving images, then the evaluation process is simple, but the relevance and suitability of selected images for layout are reduced
Solution Approach 1:
The patent segments the evaluation process into distinct pathways based on image source. One pathway handles still images with appropriate evaluation metrics, while another pathway handles moving images with different metrics. This segmentation improves selection accuracy by ensuring each image type is evaluated on its own merits, while the overall system complexity is managed through modular evaluation components.
Solution Approach 2:
The patent changes evaluation parameters dynamically based on image data source. When still images are detected, specific parameters (e.g., sharpness, lighting, composition) are applied. When moving images are detected, different parameters (e.g., motion dynamics, visual interest, engagement) are applied. This parameter adaptation improves selection accuracy without requiring a completely separate evaluation system for each image type.
3Ease of operation
If a unified evaluation method is used for all image data, then the system is easy to implement, but the user satisfaction and relevance of the generated layout is reduced
Solution Approach 1:
The patent implements universality by creating a single integrated evaluation system that can handle multiple image types through a common architectural framework. The system uses a unified scoring mechanism that incorporates both still image and moving image evaluation criteria, allowing one system to serve multiple purposes without requiring separate specialized systems for each image type, thus maintaining ease of operation while improving layout relevance.
Solution Approach 2:
The patent employs parameter changes within a unified framework, where the same overall evaluation system dynamically adjusts specific evaluation parameters based on image source detection. This allows the system to maintain a simple, easy-to-operate unified structure while achieving high layout relevance through intelligent parameter adaptation to different image types.
Data Source
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AI summary
A control method for an information processing apparatus that generates a layout image by arranging an image in a template includes making an evaluation of a first image data group acquired from acquired moving image data based on a first evaluation axis and making an evaluation of a second image data group acquired from acquired still image data based on a second evaluation axis different from the first evaluation axis.