Game Event Recognition Through Hierarchical Region Analysis
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Solution Overview
Problem
Existing methods for analyzing digital content, such as video games, are resource-intensive and latency-prone due to the complexity of gameplay and the need to identify various events, especially when limited by device capacity or latency requirements.
Innovation Solution
The approach involves analyzing specific regions of the image that are highly indicative of event occurrence, using a hierarchical region analysis method where primary regions trigger the evaluation of subordinate regions based on state changes, reducing computational load while maintaining event detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive content analysis is performed on video games, then event detection accuracy is improved, but device resource consumption increases
Solution Approach 1:
The patent divides the video content into discrete frames and identifies specific regions of interest within each frame. By segmenting the analysis into frame-level and region-level processing, the system achieves comprehensive event detection without requiring full-content analysis of every frame, thereby reducing overall computational load while maintaining detection accuracy.
Solution Approach 2:
The system applies different analysis depths to different regions of the video content. High-priority regions that are more indicative of game events receive more thorough analysis, while other areas receive lighter processing. This localized quality approach ensures accurate event detection in critical areas while conserving device resources on less important regions.
2Measurement precision
If comprehensive content analysis is performed on video games, then event detection accuracy is improved, but processing time increases
Solution Approach 1:
By segmenting the video analysis into independent frame-level and region-level processing stages, the system can process frames in sequence and identify regions of interest early, allowing subsequent processing to focus only on relevant areas. This segmentation enables parallel processing opportunities and reduces overall processing time while maintaining comprehensive event detection capability.
Solution Approach 2:
The system performs partial analysis on frames that do not contain high-priority regions, and reserves more comprehensive analysis for frames containing regions of interest. This selective depth of analysis reduces average processing time across all frames while ensuring that frames with potential game events receive the necessary thorough examination for accurate detection.
3Productivity
If hierarchical region analysis is implemented, then computational load is reduced, but system complexity increases
Solution Approach 1:
The hierarchical region analysis system is segmented into distinct functional modules: frame processing module, region identification module, and event detection module. Each module has a specific responsibility and processes data in a defined sequence, which simplifies the overall system architecture despite the sophisticated analysis it performs. This modular segmentation makes the complex system more manageable and easier to implement.
Solution Approach 2:
The system performs preliminary identification of high-priority regions before conducting detailed event detection. This preliminary action of marking regions of interest in advance allows the main event detection algorithm to focus computational resources only on relevant areas, reducing the overall computational load. The preliminary region identification step simplifies the complexity by creating a clear workflow sequence.
Data Source
AI summary
Automated detection of events in content can be performed using regions of information associated with various user interface or display elements. Certain elements can be indicative of a type of event, and regions associated with these elements can be analyzed on a per-frame basis. If one of these primary regions shows a state or transition that is indicative of one of these events, one or more secondary regions can be analyzed as well to attempt to verify whether that event occurred, as well as whether that event qualifies for selection for additional use. Selected events can be used for purposes such as to generate highlight montages, training videos, or user profiles. These events may be positioned at different layers of an event hierarchy, where child regions are only analyzed for frames where a parent region is indicative of a type of event.