Automated Emoticon Package Generation via Text Superimposition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current emoticon search systems rely on manually produced resources, resulting in high costs and long production times, limiting their efficiency and accuracy in generating relevant emoticon packages for Internet users.
Innovation Solution
An automated method for generating emoticon packages by determining associated text from emoticon pictures or similar packages, using word frequency, semantics, and recognition results to improve matching accuracy, and superimposing target text onto the images to create new emoticon packages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual production of emoticon resources is used, then the quality and accuracy of emoticon packages can be maintained, but the production period becomes long and costs increase
Solution Approach 1:
The patent replaces the manual mechanical production system with an automated computer-based system. The system uses image recognition technology to automatically identify emoticon pictures, extract features, and generate matching text descriptions, thereby eliminating the need for manual production while maintaining or improving accuracy and significantly reducing production time.
Solution Approach 2:
The system enables emoticon packages to generate their own associated text automatically through feature extraction and matching algorithms. The emoticon picture itself provides the necessary information for text generation through its visual features, eliminating the need for external manual annotation services.
2Manufacturing precision
If manual production of emoticon resources is used, then the quality of emoticon packages can be maintained, but production costs become high
Solution Approach 1:
The patent replaces expensive manual production with automated computer-based processing. The system uses efficient image recognition and text matching algorithms that consume minimal computational resources compared to human labor costs, thereby maintaining quality while significantly reducing production costs.
Solution Approach 2:
The system creates emoticon packages by copying and adapting existing successful patterns from the emoticon database. Instead of manually creating each emoticon from scratch, the system replicates proven effective structures and associations, reducing the energy and cost required for production.
3Productivity
If automated text generation is implemented, then production efficiency can be improved, but the accuracy of matching text may deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms where the extracted features from emoticon pictures are continuously refined based on matching results. The text matching process uses feedback from similarity comparisons to adjust and improve the accuracy of generated text, ensuring that automated production maintains high precision while achieving improved efficiency.
Solution Approach 2:
The patent introduces feature extraction and text matching algorithms as intermediaries between the emoticon picture and the final text description. These intermediaries process the visual information through multiple stages (feature extraction, similarity comparison, text selection) to ensure accurate matching while maintaining high production efficiency.
Data Source
AI summary
Provided are an emoticon package generation method and apparatus, a device and a medium which relate to the field of graphic processing and in particular to Internet technologies. The specific implementation solution is: determining at least one of associated text of an emoticon picture or a similar emoticon package of an emoticon picture, where the associated text of the emoticon picture includes at least one of main part information, scenario information, emotion information, action information or connotation information; determining target matching text from the at least one of the associated text of the emoticon picture or associated text of the similar emoticon package; and superimposing the target matching text on the emoticon picture to generate a new emoticon package.