AR Hand-Tracking Pipeline Dimming for Low-Power Gesture Wake-Up
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Solution Overview
Problem
AR systems face challenges with limited user input modalities and power conservation, as they often require complex interactions and consume significant power for hand gesture recognition, which is not feasible in low power modes.
Innovation Solution
A hand-tracking input pipeline for AR systems that dims most components to conserve power, activating only when a gesture is initiated, using a binary gesture classifier to detect gesture initiation with minimal computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the hand-tracking input pipeline operates in full operation mode, then user interaction capability is improved, but power consumption increases
Solution Approach 1:
The hand-tracking input pipeline transitions between different operational states (deactivated, dimmed, full operation) based on detected user needs. The system dynamically adjusts its functionality by activating the binary gesture classifier in dimmed mode to detect gesture initiation, then transitioning to full operation mode when interaction is required, and returning to deactivated mode when idle.
Solution Approach 2:
Instead of operating at full capacity continuously or not at all, the system uses partial action by implementing a dimmed mode where only essential components (camera and binary gesture classifier) operate at reduced capacity. This allows the system to maintain basic gesture detection capability while consuming significantly less power than full operation mode.
2Use of energy by moving object
If the hand-tracking input pipeline is deactivated to conserve power, then power consumption is reduced, but user interaction responsiveness deteriorates
Solution Approach 1:
The binary gesture classifier operates in dimmed mode continuously to detect gesture initiation before full hand-tracking processing is activated. This preliminary detection mechanism ensures that when a user begins a gesture, the system is already aware and can quickly transition to full operation mode, maintaining responsiveness without requiring continuous full-power operation.
Solution Approach 2:
The binary gesture classifier serves as an intermediary component that bridges the gap between the deactivated state and full operation mode. It operates with minimal computational resources to detect when user interaction is about to occur, then triggers the activation of the complete hand-tracking pipeline, ensuring smooth transitions and maintaining interaction reliability.
3Use of energy by stationary object
If a binary gesture classifier is used for gesture initiation detection, then computational resource usage is reduced, but gesture recognition precision may be compromised
Solution Approach 1:
The gesture recognition process is segmented into two distinct stages: first, the binary gesture classifier detects gesture initiation with minimal computational resources; second, the full hand-tracking input pipeline processes the complete gesture with higher precision. This segmentation allows each component to be optimized for its specific function, balancing resource usage and precision.
Solution Approach 2:
Different levels of processing precision are applied at different stages of gesture detection. The binary gesture classifier uses simplified algorithms suitable for its specific task of detecting initiation, while the full hand-tracking pipeline applies more sophisticated processing only when needed, achieving high precision for the specific subtask of initiation detection without requiring full computational resources continuously.
Data Source
AI summary
A hand-tracking input pipeline dimming system for an AR system is provided. The AR system deactivates the hand-tracking input pipeline and places a camera component of the hand-tracking input pipeline in a limited operational mode. The AR system uses the camera component to detect initiation of a gesture by a user of the AR system and in response to detecting the initiation of the gesture, the AR system activates the hand-tracking input pipeline and places the camera component in a fully operational mode.