Touch and Non-Touch Gesture Detection Using Differential Thresholds
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Solution Overview
Problem
Current man-machine interfaces, while improved, still face challenges in seamlessly integrating touch and non-touch gestures for efficient user interaction with computing devices, often requiring specific detection systems and thresholds that can be context-dependent and require calibration.
Innovation Solution
A computer interface system that combines touch and non-touch gesture detection systems using multiple cameras and light emitters, allowing for the generation of similarity values and differential threshold comparisons to select the most accurate gesture input, enabling the integration of both gesture types for unified user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate touch and non-touch gesture detection systems are used, then gesture detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system divides gesture detection into separate touch-based and non-touch-based detection systems, each optimized for its specific gesture type. The touch-based system uses touch-sensitive surface data while the non-touch system uses camera-based gesture recognition, allowing each subsystem to specialize in detecting its optimal gesture type without interference from the other.
Solution Approach 2:
The patent combines the outputs of separate touch and non-touch detection systems into a unified gesture recognition approach. The system integrates detection results from both modalities, using similarity values and thresholds to determine which gesture type was intended, thereby achieving comprehensive gesture detection capability while maintaining the benefits of specialized detection systems.
2Adaptability or versatility
If multiple detection systems with different thresholds are used, then gesture recognition adaptability is improved, but ease of operation decreases
Solution Approach 1:
The system incorporates feedback mechanisms where detection results from both touch and non-touch systems are continuously monitored and compared. Similarity values are calculated and fed back into the decision-making process, allowing the system to automatically adjust which detection system's output is prioritized based on the current interaction context, reducing the need for manual threshold adjustment.
Solution Approach 2:
The patent dynamically adjusts detection parameters and thresholds based on the interaction context. The system can switch between different detection modalities and adjust similarity thresholds automatically, allowing the same interface to adapt to different user interaction styles without requiring users to manually configure operational parameters.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances user interaction by allowing for a more intuitive and adaptive interface that can accurately detect and interpret a wide range of gestures, improving usability and reducing ambiguity in gesture recognition.
Implementation Method 1
A computer interface system that combines touch and non-touch gesture detection systems using multiple cameras and light emitters
Data Source
AI summary
A computer interface may use touch- and non-touch-based gesture detection systems to detect touch and non-touch gestures on a computing device. The systems may each capture an image, and interpret the image as corresponding to a predetermined gesture. The systems may also generate similarity values to indicate the strength of a match between a captured image and corresponding gesture, and the system may combine gesture identifications from both touch- and non-touch-based gesture identification systems to ultimately determine the gesture. A threshold comparison algorithm may be used to apply different thresholds for different gesture detection systems and gesture types.