Image Grouping by Shooting Interval Evaluation
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Solution Overview
Problem
Existing image grouping techniques are influenced by image taking conditions and lack consideration for unity and variations in the number of images within groups, resulting in groups that may not exhibit cohesion.
Innovation Solution
An image information processing apparatus and method that evaluates shooting interval variations and uses a grouping unit to divide or merge image data pieces based on shooting intervals, with an evaluation unit calculating scores and a determination unit selecting optimal grouping steps to form cohesive groups unaffected by image taking conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If images are grouped according to shooting time and temporal interval variations, then the grouping process is simple and fast, but the resulting groups lack unity and are greatly influenced by image taking conditions
Solution Approach 1:
The patent introduces an evaluation mechanism that calculates scores for each grouping step based on multiple evaluation items (shooting interval variation, image quality variation, subject variation). This feedback loop allows the system to assess grouping quality and select optimal grouping steps, transforming the simple temporal interval-based grouping into a quality-controlled process that maintains speed while improving reliability.
Solution Approach 2:
The patent changes the grouping parameters from solely temporal intervals to a composite evaluation system incorporating shooting interval variation, image quality variation, and subject variation. By adjusting these parameters and their weights, the system can control both grouping speed and quality, resolving the contradiction between simple fast grouping and reliable quality grouping.
2Reliability
If multiple evaluation items are used to assess grouping steps, then grouping quality improves, but computational complexity increases
Solution Approach 1:
The patent segments the evaluation process into distinct evaluation items (shooting interval variation, image quality variation, subject variation), each handled by separate calculation modules. This segmentation allows the complex evaluation to be broken down into manageable, independent components that can be processed efficiently, reducing overall computational complexity while maintaining comprehensive quality assessment.
Solution Approach 2:
The patent implements a flexible evaluation system where not all evaluation items need to be applied with equal weight in all situations. The system can selectively apply evaluation items based on specific requirements, performing partial evaluation when full evaluation is unnecessary, thus reducing computational complexity while maintaining grouping quality when needed.
3Adaptability or versatility
If grouping steps sequentially divide or merge image data pieces, then flexible grouping is achieved, but determining the optimal grouping step becomes difficult
Solution Approach 1:
The patent applies feedback by calculating scores for each grouping step based on multiple evaluation criteria and using these scores to identify optimal grouping steps. The determination unit selects grouping steps with scores meeting predetermined thresholds, providing an automated feedback mechanism that simplifies optimal step identification while maintaining grouping flexibility.
Solution Approach 2:
The patent changes the approach to identifying optimal grouping steps by introducing score-based selection criteria. Instead of difficulty in detecting optimal steps, the system transforms the problem into evaluating and comparing quantitative scores, making optimal step identification systematic and measurable while preserving the flexibility of sequential grouping operations.
Data Source
AI summary
An apparatus for processing image information regarding image data pieces each having retrievable information including shooting time and a shooting interval includes a grouping unit configured to group the image data pieces, which are arranged in order of the shooting time, by sequentially carrying out grouping steps that each divide or merge the image data pieces into groups according to the shooting intervals, an evaluation unit configured to calculate a score for each of the grouping steps according to one or a plurality of predetermined evaluation items, and a determination unit configured to determine a specific one of the grouping steps according to the calculated scores.