Three-State Gesture Model for Artificial Reality Hand Interaction
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Solution Overview
Problem
Existing artificial reality systems inaccurately interpret hand postures as input gestures, leading to unintended interactions and inefficiencies, as they lack a gating mechanism to differentiate between normal hand movements and intended input gestures.
Innovation Solution
A three-state model is implemented for hand interaction systems, comprising a neutral state for monitoring, a tracking state for gesture signaling, and an active state for input recognition, which reduces misinterpretation by requiring a transition from neutral to tracking and then active states for gesture recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If hand gestures are continuously monitored for input interactions, then user interaction responsiveness is improved, but misinterpretation of normal hand movements as input gestures increases
Solution Approach 1:
The system performs preliminary actions by transitioning through intermediate states before executing gestures. Users must first transition to a tracking state where the hand is detected, then to an active state where gestures are recognized. This preliminary state transition mechanism filters out normal hand movements that don't follow the proper sequence, reducing misinterpretation while maintaining responsiveness.
Solution Approach 2:
The system dynamically adjusts its monitoring behavior based on the current state. In the neutral state, the system monitors for entry to tracking state. In the tracking state, it monitors for transition to active state. In the active state, it monitors for gesture completion. This dynamic state-dependent monitoring allows the system to be responsive to valid gestures while being selective about what constitutes a valid interaction sequence.
2Reliability
If a three-state model with multiple transition requirements is implemented, then gesture recognition accuracy is improved, but system complexity increases
Solution Approach 1:
The gesture recognition system is segmented into distinct states (neutral, tracking, active) with clear transition criteria between each. Each state has a specific monitoring function, and transitions are governed by defined conditions. This segmentation breaks down the complex gesture recognition task into manageable pieces, making the overall system more maintainable and easier to implement despite the increased state management.
3Speed
If continuous hand monitoring is performed without state gating, then interaction speed is improved, but power consumption increases
Solution Approach 1:
The system employs periodic state transitions rather than continuous full-monitoring. The hand tracking operates at different levels of intensity depending on the state: in neutral state it monitors for entry conditions, in tracking state it monitors for gesture activation, and in active state it processes gestures. This periodic/state-dependent monitoring maintains interaction speed while reducing overall power consumption compared to continuous full-monitoring.
Data Source
AI summary
A hand interaction system can use a three-state model to differentiate between normal hand movements, such as reaching for an object, and hand input gestures. The three-state model can specify a sequence of states including: 1) a neutral state, 2) a tracking state, and 3) an active state. In the neutral state, the hand interaction system monitors for a gesture signaling a transition to the tracking state but does not otherwise interpret a gesture corresponding to the active state as input. Once a gesture causes a transition to the intermediate tracking state, the hand interaction system can recognize a further active state transition gesture, allowing active state interaction. Thus, the monitoring for the intermediate tracking state provides a gating mechanism, making it less likely that the hand interaction system will interpret hand movements as input when not so intended by the user.