Image Ranking and Selection Using Multi-Characteristic Scoring
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Solution Overview
Problem
Existing systems lack an efficient method to automatically rank and select high-quality images from large collections based on multiple characteristics such as visual capture, social popularity, and visual content, often requiring significant computational resources and manual effort.
Innovation Solution
A computer-implemented method that examines images for visual capture characteristics, social popularity characteristics, and visual content characteristics, assigns individual scores, and determines overall scores to rank and select images for display, using a processor to weight characteristics and exclude undesirable content types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple image characteristics are examined and scored to determine rankings, then image selection quality is improved, but computational resource consumption increases
Solution Approach 1:
The patent segments the image evaluation process into distinct characteristic categories (visual capture characteristics, visual content characteristics, and social popularity characteristics), each evaluated independently and scored separately. This segmentation allows the system to process multiple characteristics in an organized manner, improving selection quality while managing computational resources through structured evaluation.
Solution Approach 2:
The patent applies parameter changes by assigning different weights to individual characteristic scores when determining overall image rankings. By adjusting these weight parameters, the system can optimize the balance between comprehensive evaluation quality and computational efficiency, allowing flexible control over resource consumption based on specific application needs.
2Measurement precision
If comprehensive image characteristics are evaluated, then ranking accuracy is improved, but processing time increases
Solution Approach 1:
The patent implements preliminary action by pre-defining the three main characteristic categories and their sub-characteristics before the actual image evaluation process. This preliminary structuring allows for efficient processing during execution, as the evaluation framework is already established, reducing processing time while maintaining comprehensive and accurate ranking results.
Solution Approach 2:
The system uses parameter changes by allowing flexible weighting of different characteristic scores. This enables optimization of processing time by adjusting which characteristics receive higher weights based on specific application requirements, thereby achieving accurate rankings without always processing all characteristics at maximum depth.
3Productivity
If manual image selection is replaced with automated scoring, then productivity is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling the system to automatically evaluate and rank images without human intervention. The automated scoring mechanism examines multiple characteristics, calculates individual scores, and determines final rankings independently, dramatically improving productivity. The system serves itself by using predefined algorithms and weightings to make selection decisions that previously required manual human review.
Solution Approach 2:
The patent manages system complexity through parameter changes by allowing flexible adjustment of characteristic weights and evaluation criteria. This parametric approach enables the system to adapt to different application needs without requiring fundamental redesign, thereby improving productivity while keeping the system manageable through configurable parameters rather than hard-coded complex logic.
Data Source
AI summary
Implementations generally relate to ranking and selecting images for display from a set of images. In some implementations, a computer-implemented method includes providing selected images for display, including examining characteristics of a plurality of images, where the examined characteristics include two or more of: visual capture characteristics, visual content characteristics, and social popularity characteristics of the images. The method determines individual scores for the respective examined characteristics of the images, determines overall scores of the images based on a combination of the individual scores for the examined characteristics of the images, and determines a ranking of the images based on the overall scores. The method selects one or more images based on the ranking of the images, and causes a display of the one or more selected images.