Selective Image Summarization With Priority-Based AI Processing
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Solution Overview
Problem
Users face challenges in efficiently managing and retrieving digital images on personal devices due to limited metadata and high computational demands of conventional AI-based solutions, leading to time-consuming manual scrolling and resource constraints.
Innovation Solution
Implementing a system that intelligently prioritizes images for summarization using generative AI models, offloads processing tasks, and integrates metadata to generate personalized summaries, while efficiently managing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional AI-based solutions are used to analyze images, then image summarization capability is improved, but computational resources and processing time are excessively consumed
Solution Approach 1:
The patent segments the image analysis task by first dividing images into groups based on visual similarity and redundancy, then selectively applying generative AI summarization only to representative images from each group rather than processing all images individually. This segmentation approach reduces computational resources while maintaining comprehensive summarization coverage.
Solution Approach 2:
The patent applies partial action by selecting only a subset of images for detailed AI-based summarization rather than processing all images with full AI analysis. Images are prioritized based on metadata indicators such as view frequency, share frequency, and user interactions, ensuring that AI resources are allocated to the most valuable images while less important images are handled with lighter processing.
2Reliability
If all images are processed with AI summarization, then comprehensive image analysis is achieved, but processing time increases significantly
Solution Approach 1:
The patent performs preliminary actions by first grouping images based on visual similarity and redundancy before applying AI summarization. This preliminary organization allows the system to identify representative images that can stand in for multiple similar images, reducing the total number of AI processing operations needed while maintaining comprehensive analysis coverage.
Solution Approach 2:
The patent applies local quality by providing detailed AI summarization only to images with high priority indicators (such as frequent views, shares, or user interactions) while using lighter processing for lower priority images. This differentiated approach ensures comprehensive analysis of the most important images without uniformly expending resources on all images.
3Loss of information
If metadata is enhanced with AI-generated summaries, then image searchability and context are improved, but device resource consumption increases
Solution Approach 1:
The patent extracts key information from images using AI models only when necessary, such as when images have high priority indicators or when users interact with them. The system extracts and stores only the most relevant summary information in metadata rather than processing all image data, reducing device resource consumption while maintaining enhanced searchability and context for important images.
Data Source
AI summary
Various embodiments include computing devices and methods for managing and analyzing digital images in the computing device. Various embodiments may include selecting an image from a plurality of images, determining a processing priority for the selected image, and generating a summary for the selected image. The methods may further include customizing the generated summary to provide a customized summary based on one or more subjects in the image, a user profile, user relationships to the one or more subjects in the image, and user-based context information. The methods may further include updating metadata associated with the selected image based on the customized summary and storing the selected image and associated metadata in memory.