Gameplay Event Tracking Using Perceptual Hash Scene Matching
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Solution Overview
Problem
It is difficult for users to simultaneously play video games and selectively record exciting or surprising content while also summarizing game progress, as identifying significant events within the generated gameplay footage is challenging due to the vast amount of user-directed content.
Innovation Solution
An apparatus and method for video tracking that uses perceptual hashing to detect scene cuts and identify notable events in gameplay by comparing image hashes, utilizing a database of hashes associated with predefined game events, and employing key points for additional verification to reduce computational overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually review and identify significant events in gameplay footage, then event identification accuracy is improved, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system automatically performs event identification without requiring manual user intervention. The processor autonomously compares perceptual hashes of gameplay images against a database of event hashes, identifies matches, and generates summaries independently, eliminating the need for users to manually review footage while maintaining high accuracy through algorithmic precision
Solution Approach 2:
The patent replaces the mechanical process of manual event identification with an automated computational system using perceptual hashing and image comparison algorithms. This substitution transforms the manual review process into an automated digital processing workflow, dramatically reducing time consumption while preserving identification accuracy through sophisticated hash matching techniques
2Reliability
If comprehensive gameplay footage is recorded to capture all potential events, then event detection completeness is improved, but data storage requirements and processing complexity increase
Solution Approach 1:
The system extracts only the essential perceptual features of gameplay images by converting them into compact perceptual hashes. Instead of storing and processing entire high-resolution gameplay footage, the system extracts and compares hash representations, dramatically reducing data storage requirements while maintaining the ability to detect all significant events through hash matching against the database
3Measurement precision
If detailed image comparison is performed to accurately identify events, then event identification precision is improved, but computational overhead and processing time increase
Solution Approach 1:
The patent replaces computationally intensive pixel-by-pixel image comparison with a more efficient perceptual hashing mechanism. The system substitutes detailed mechanical image analysis with hash-based pattern matching, achieving high identification precision through compact feature representation while dramatically reducing computational overhead and energy consumption
4Measurement precision
If manual summarization of game progress is performed, then summary accuracy is improved, but productivity and time efficiency decrease
Solution Approach 1:
The system automatically generates gameplay summaries without requiring manual user effort. The processor independently identifies matched events, extracts relevant information, and compiles summaries of game progress autonomously, maintaining high summary accuracy through precise hash matching while dramatically improving productivity by eliminating manual summarization tasks
Data Source
AI summary
A method of identifying an event that is graphically acknowledged within a sequence of images, comprises the steps of defining one or more regions of respective images in which a graphical indication of acknowledgement will occur, selecting at least a first defined region as a candidate acknowledgement image, and selecting for output one or more of the candidate acknowledgement images, or respective images of the sequence of images that comprise such candidate acknowledgement images.