Photo Summary System Using Attribute Classification and User Ratios
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Solution Overview
Problem
Organizing and summarizing large volumes of digital photos based on user preferences and attributes is tedious and time-consuming, especially when dealing with thousands of images covering various events, locations, and themes.
Innovation Solution
A photo summary system that classifies photos into categories using predefined attributes, allows user input for criteria through a controller, and selects subsets based on user-defined ratios and preferences to generate a summary of photos, which can be displayed as an album or shared online.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual organizing of photos is performed, then photo summaries can be customized according to user preferences, but the process becomes tedious and time-consuming
Solution Approach 1:
The system enables self-service by automatically classifying photos into categories using predefined attributes (such as people, places, events) and autonomously selecting representative photos based on user-defined criteria and ratios, eliminating the need for manual photo-by-photo review while still allowing users to customize summary compositions through simple parameter setting
Solution Approach 2:
The system performs preliminary classification of all photos into organized categories using predefined attributes before the user creates a summary. This pre-organization allows users to quickly generate customized summaries by simply selecting categories and specifying ratios, without needing to manually sort through entire photo collections each time
2Productivity
If automatic photo organization is implemented, then time consumption is reduced, but the system complexity increases
Solution Approach 1:
The system segments the photo collection into distinct categories based on predefined attributes (people, places, events, etc.). This segmentation allows the complex task of summarizing large photo collections to be broken down into manageable category-based selections, simplifying the overall process while maintaining high productivity
Solution Approach 2:
The system uses parameter changes by allowing users to define selection criteria through adjustable ratios for different categories. Instead of complex algorithms, the system responds to simple parameter inputs (category selection and ratio specification) to automatically generate summaries, maintaining low operational complexity while achieving high productivity
3Measurement precision
If photos are classified into multiple categories, then photo selection precision is improved, but the device complexity increases
Solution Approach 1:
The classifier is designed with multi-functionality by using a single set of predefined attributes (people, places, events, objects, activities) to perform multiple classification tasks across different photo categories. This universal classification approach improves precision without requiring separate complex classifiers for each category, thereby limiting the increase in device complexity
Data Source
AI summary
Systems and methods for generating a summary of photos from a plurality of received photos are described. The received photos are classified according to predefined attributes. Two or more of the categories are selected, and a ratio value is received from a user relating to the two or more of the categories. Photos are selected from among the photos in the two or more categories based on the specified ratio and based on sorting the received photos according to time information. The selected photos comprising the summary of photos are displayed.