Real-Time Image Composition Guidance Using Deep Learning
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Solution Overview
Problem
Existing image composition guidance solutions for mobile devices lack real-time feedback and efficient resource utilization, leading to inefficient use of processing power and memory, and do not provide intuitive user interfaces for improving photo composition.
Innovation Solution
A deep-learning system is integrated into an image processing application that provides real-time composition guidance and crop recommendations by analyzing image data from a camera's field of view, allowing users to preview and select improved compositions without storing intermediate images, thus optimizing resource use and offering intuitive user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing composition guidance solutions perform edits by taking and storing intermediate images, then composition improvement is achieved, but processing power, memory, cache, and power are wastefully consumed
Solution Approach 1:
The patent uses virtual copies and previews of image compositions instead of storing actual intermediate image files. The system generates virtual representations of cropped and zoomed versions for user review, eliminating the need to save multiple intermediate image copies to storage memory.
Solution Approach 2:
The patent replaces the mechanical process of physically storing intermediate image files with a computational approach using virtual memory and processing buffers. The system uses efficient image processing algorithms that operate in memory without requiring persistent storage of intermediate results.
2Manufacturing precision
If existing composition guidance solutions require user experimentation time, then composition improvement is achieved, but the user cannot retake the original picture and may lose the desired scene
Solution Approach 1:
The patent performs composition analysis and generates crop/zoom suggestions in real-time as the user captures the image, rather than requiring post-capture editing. The system provides immediate feedback on composition quality and suggested improvements before the user finalizes the shot.
Solution Approach 2:
The patent implements real-time feedback mechanisms that provide composition scores and visual guidance overlays during image capture. The system continuously monitors composition metrics and provides immediate suggestions for improvement, allowing users to adjust their framing before taking the final photograph.
3Manufacturing precision
If existing composition guidance solutions use complex processing, then composition improvement is achieved, but the user interface becomes cumbersome and not intuitive
Solution Approach 1:
The patent implements automated composition analysis that performs complex evaluation without requiring user intervention. The system automatically calculates composition scores, identifies framing issues, and generates correction suggestions, eliminating the need for users to manually analyze or adjust multiple parameters.
Solution Approach 2:
The patent uses visual overlays and color-coded indicators to communicate composition quality and suggestions intuitively. The system employs graphical elements such as colored borders, highlight regions, and visual scoring indicators that provide immediate, easy-to-understand feedback without requiring complex user interaction.
Data Source
AI summary
Various embodiments describe facilitating real-time crops on an image. In an example, an image processing application executed on a device receives image data corresponding to a field of view of a camera of the device. The image processing application renders a major view on a display of the device in a preview mode. The major view presents a previewed image based on the image data. The image processing application receives a composition score of a cropped image from a deep-learning system. The image processing application renders a sub-view presenting the cropped image based on the composition score in a preview mode. Based on a user interaction, the image processing application renders the cropped image in the major view with the sub-view in the preview mode.