Gesture Judgment Using Multiple Motion History Images
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Solution Overview
Problem
Gesture judgment based on a single motion history image (MHI) often leads to misjudgment due to uncertainty in determining the direction of gesture motion, resulting in erroneous direction outputs for gesture control.
Innovation Solution
A method that analyzes multiple MHIs and employs auxiliary judgment criteria, including weight assignment and threshold settings for continuous MHI angles/directions, to accurately determine the gesture direction, considering the validity of gesture control and accounting for user habits and environmental factors like background IR calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If gesture judgment is based on a single MHI, then the processing speed is fast, but the judgment accuracy deteriorates due to uncertainty in determining gesture motion direction
Solution Approach 1:
The patent segments the gesture judgment process into multiple stages: obtaining multiple MHIs from continuous frames, extracting motion directions from each MHI, filtering invalid directions using auxiliary judgment criteria, and synthesizing the final gesture direction. This segmentation allows accurate gesture recognition by analyzing motion history across multiple time points rather than relying on a single MHI.
Solution Approach 2:
The patent applies preliminary action by establishing auxiliary judgment criteria before final gesture determination. These criteria include validating motion direction consistency across multiple MHIs, checking whether detected motions meet minimum threshold requirements, and filtering out unreliable motion directions before synthesizing the final gesture direction. This preliminary validation ensures that only reliable motion information contributes to the final judgment.
2Reliability
If multiple MHIs are analyzed with auxiliary judgment criteria, then the gesture judgment accuracy is improved, but the processing time and computational load increase
Solution Approach 1:
The patent implements partial action by selectively processing only the necessary MHIs and motion directions required for accurate gesture judgment. The auxiliary judgment criteria filter out invalid or redundant motion information, processing only the essential subset of data needed to determine gesture validity and direction, thus reducing unnecessary computational overhead.
Solution Approach 2:
The system performs self-service through automatic validation and filtering of motion directions using predefined auxiliary criteria. The gesture judgment system autonomously identifies and eliminates invalid motions based on consistency checks and threshold validations, reducing the need for manual intervention or complex external processing while maintaining high reliability.
3Measurement precision
If motion directions from multiple MHIs are obtained, then the gesture direction can be determined more accurately, but the complexity of judgment criteria increases
Solution Approach 1:
The patent changes parameters by transforming multiple motion direction measurements into a unified gesture direction determination through weighted synthesis. The auxiliary judgment criteria evaluate motion consistency, direction stability, and temporal patterns, converting complex multi-dimensional motion data into a reliable final gesture direction by adjusting and synthesizing directional parameters across multiple MHIs.
Data Source
AI summary
A gesture judgment method used in an electronic device having frame capturing function is provided. A plurality of MHI (motion history image) angles/directions are obtained from a plurality of corresponding MHIs. Whether a current gesture control is valid is judged according to the MHI angles/directions. If the current gesture control is valid, then weight assignment is performed on the MHI angles/directions to obtain a judgment result of the current gesture control.