Multimodal Gesture Detection With False Trigger Suppression
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Multimodal, multi-camera extended reality environments face challenges in hand gesture detection due to high hand velocity, field of view limitations, and landmark visibility issues, leading to false triggers and releases, which disrupt user interactions and reduce reliability.
Innovation Solution
Adaptive suppression mechanisms are employed to enhance gesture detection accuracy and reliability by utilizing multiple sensor modalities and intelligent signal validation techniques, including hand velocity-based, 2D position-based, and key landmark visibility-based suppression to minimize false triggers and releases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors and cameras are incorporated to capture a comprehensive view, then the accuracy and robustness of hand tracking and gesture recognition are improved, but the device complexity increases
Solution Approach 1:
The patent divides the gesture detection system into separate functional modules: hand tracking module, gesture detection module, and suppression mechanism module. Each module processes specific aspects of the data from multiple sensors independently, then integrates results through coordinated communication, reducing the complexity of processing all sensor data through a single complex system
Solution Approach 2:
The system uses a unified multi-camera and multi-sensor architecture that serves multiple functions: capturing hand gestures, tracking hand movement, detecting gestures, and validating through suppression mechanisms. The same hardware infrastructure supports all these functions, avoiding the need for separate dedicated systems for each function
2Productivity
If hand tracking algorithms operate continuously to provide real-time data, then the responsiveness of the system is improved, but the computational resources consumed increase
Solution Approach 1:
The patent extracts and removes false triggers and false releases from the gesture detection output through suppression mechanisms. By filtering out erroneous detections before they are processed further, the system reduces the computational burden on subsequent processing stages while maintaining real-time responsiveness
Solution Approach 2:
The system implements feedback loops where the suppression mechanism receives continuous input from hand tracking and gesture detection, adjusts its suppression thresholds and parameters based on detected patterns, and feeds back corrected gestures to the interaction system. This feedback enables adaptive computational resource allocation
3Reliability
If adaptive suppression mechanisms are implemented to reduce false triggers, then the reliability of gesture detection is improved, but the processing time increases
Solution Approach 1:
The suppression mechanism performs preliminary validation of gesture detections against established criteria (such as minimum duration thresholds, velocity thresholds, and spatial consistency checks) before gestures are finalized. This preliminary action filters out obviously false detections early in the processing pipeline, preventing them from consuming further computational resources
Solution Approach 2:
The system dynamically adjusts suppression thresholds and parameters based on real-time conditions such as hand movement velocity, camera field of view, and detected gesture context. During high-velocity movements or edge field of view conditions, suppression is intensified; during stable conditions, suppression is reduced, optimizing processing time while maintaining reliability
Data Source
AI summary
A multi-camera, multimodal gesture detection system for augmented reality devices combines outputs from multiple image sensors, using different modalities, to generate fused gesture detection trigger signals and gesture detection release signals. The system processes fused trigger signals using a trigger suspension component, which suppresses false triggers based on hand velocity, position of a detected hand within a field of view of an image sensor, and visibility of key hand landmarks. The system processes fused release signals using a release suspension component, which suppresses false release signals based on hand velocity, position of a detected hand within a field of view of an image sensor, and visibility of key hand landmarks. This approach enhances gesture detection accuracy and reliability in challenging environments.