Gesture Confidence Adjustment via Compatibility Metrics
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Solution Overview
Problem
Gesture detection systems struggle to accurately interpret user gestures in three-dimensional space due to variations in how users perform motions, leading to misinterpretation of intended electronic commands, especially for devices configured to detect three-dimensional motions.
Innovation Solution
A gesture detection device that generates a confidence score for detected gestures and adjusts it based on compatibility metrics derived from comparisons with prior gestures, using a gesture pair database to determine affinity or repellent pairs, thereby refining the execution of electronic commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If gesture devices detect three-dimensional motions to enable versatile gesture control, then the adaptability and functionality of the device improve, but the difficulty of detecting and measuring gestures accurately increases due to user variation
Solution Approach 1:
The system generates confidence scores for detected gestures and uses feedback from gesture sequence analysis to adjust these scores. By comparing each gesture with previous gestures and evaluating compatibility metrics, the system refines its detection accuracy over time, resolving the contradiction between versatile detection capability and measurement accuracy.
Solution Approach 2:
The system pre-establishes a gesture pair database containing affinity and repellent relationships between different gestures. This preliminary preparation allows the system to quickly evaluate gesture compatibility and adjust confidence scores without real-time complex computation, improving both detection accuracy and processing efficiency.
2Device complexity
If the gesture device uses a fixed confidence threshold for command execution, then the device complexity remains low, but the reliability of gesture interpretation decreases due to user variations
Solution Approach 1:
The system dynamically adjusts confidence thresholds based on gesture sequence context and compatibility metrics. Instead of using a fixed threshold, the threshold adapts to the specific gesture pattern being recognized, improving reliability while maintaining manageable complexity through rule-based adjustment mechanisms.
Solution Approach 2:
The system changes the confidence threshold parameter dynamically based on the compatibility between detected gestures and expected gesture sequences. By adjusting this parameter according to contextual information from the gesture pair database, the system improves interpretation reliability without requiring a complete redesign of the recognition architecture.
3Measurement precision
If the system adjusts confidence scores based on gesture compatibility metrics, then the accuracy of gesture interpretation improves, but the computational processing time increases
Solution Approach 1:
The system pre-computes and stores gesture compatibility relationships in a gesture pair database before runtime. By preparing affinity and repellent gesture pairs in advance, the system avoids complex real-time calculations during gesture recognition, reducing processing time while maintaining high interpretation accuracy.
Solution Approach 2:
The system applies confidence score adjustment selectively based on gesture compatibility rather than uniformly for all gestures. By focusing computational resources on adjusting scores only when compatibility metrics indicate potential ambiguity, the system improves accuracy for critical cases while minimizing overall processing time.
Data Source
AI summary
Techniques are provided for a gesture device to detect a series of gestures performed by a user and execute corresponding electronic commands associated with the gestures. The gesture device detects a gesture constituting movements from a user in three-dimensional space and generates a confidence score value for the gesture. The gesture device selects an electronic command associated with the gesture and compares the electronic command with a prior electronic command associated with a prior gesture previously detected by the gesture device in order to determine a compatibility metric between the electronic command and the prior electronic command. The gesture device then adjusts the confidence score value based on the compatibility metric to obtain a modified confidence score value. The electronic command is executed by the gesture device when the modified confidence score value is greater than a predetermined threshold confidence score value.