Subject Composition Overlay for Image Display
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Solution Overview
Problem
Amateur photographers lack knowledge on effective image composition, resulting in unbalanced and uninteresting images due to inadequate distribution and posing of subjects, which is computationally intractable for conventional camera processors.
Innovation Solution
A system and method that calculates a distinctive subject distribution and determines subject poses, using data structures and neural networks to reduce computational complexity, allowing for enhanced image composition by overlaying the subject composition on the camera display, enabling photographers to adjust subject placement before capturing the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional camera processors are used for calculating subject distribution and poses, then device complexity is reduced, but manufacturing precision of image composition deteriorates
Solution Approach 1:
The patent segments the image composition task into distinct modules: subject detection, pose estimation, and composition calculation. Each module operates independently with specialized algorithms, allowing complex composition quality to be achieved without requiring a monolithic complex processor. The segmentation enables distributed computation across available hardware resources.
Solution Approach 2:
The system performs preliminary detection and estimation operations before final composition rendering. Subject detection and pose estimation are completed in advance, with results stored for use in the composition calculation phase. This preliminary action reduces the real-time computational burden on the camera processor while maintaining high composition quality.
2Manufacturing precision
If detailed subject distribution calculation is performed, then image composition quality is improved, but processing time increases
Solution Approach 1:
The patent implements a multi-level composition calculation approach where basic subject distribution is calculated for all subjects, and detailed pose-specific distribution is calculated only for selected subjects that require enhanced positioning. This partial action approach achieves high overall composition quality without performing excessive detailed calculations on every subject, thereby reducing total processing time.
Solution Approach 2:
Different levels of calculation precision are applied to different subjects based on their importance and pose complexity. Critical subjects receive detailed distribution calculation while less important subjects use simplified positioning. This local quality differentiation maintains high composition accuracy for key elements while reducing overall processing time.
Data Source
AI summary
For displaying a subject composition, a method determines a subject number, a subject age category, and a subject size for one or more subjects of an image. The method further calculates a subject distribution that indicates a position for a face of each subject. In addition, the method determines a subject pose for each subject that indicates a body position for the subject. The method further displays the subject composition comprising the subject distribution and the subject poses overlaying a display image.