AR Wrist Gesture Navigation for Responsive Virtual Scrolling
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Solution Overview
Problem
Existing navigation and scrolling techniques in computer-generated shared artificial reality environments lack responsiveness and intuitiveness, particularly in interacting with scrollable lists, hindering a natural user experience.
Innovation Solution
Implementing wrist movement-based input gestures, such as flexion, extension, pronation, supination, radial, and ulnar movements, to translate into navigation commands and scrolling parameters, enhancing the natural and intuitive interaction with virtual objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional navigation and scrolling techniques are used in artificial reality environments, then the system structure remains simple, but the responsiveness and intuitiveness of interaction deteriorate
Solution Approach 1:
The patent replaces traditional mechanical input devices (controllers, keyboards) with direct hand gesture recognition. The system uses computer vision and motion tracking to capture hand movements and translate them into navigation commands, eliminating the need for physical intermediaries and creating more intuitive interaction.
Solution Approach 2:
The patent introduces a gesture recognition system as an intermediary between the user's natural hand movements and the virtual environment navigation. This mediator translates complex hand gestures into standardized navigation commands, bridging the gap between natural human motion and digital interface requirements.
2Ease of operation
If wrist movement-based input gestures are implemented, then the intuitiveness of interaction improves, but the difficulty of detecting and measuring gestures increases
Solution Approach 1:
The patent employs a multi-functional tracking system that can detect various types of wrist movements (flexion, extension, pronation, supination, radial, and ulnar deviations) using the same underlying technology platform. This universal approach handles diverse gesture types through unified detection algorithms.
Solution Approach 2:
The patent segments wrist movement detection into distinct anatomical components (flexion/extension, pronation/supination, radial/ulnar deviations), allowing the system to independently track and interpret each degree of freedom. This segmentation simplifies the complex task of overall gesture recognition by breaking it into manageable directional components.
3Adaptability or versatility
If multiple types of wrist movements are recognized, then the versatility of navigation control improves, but the device complexity increases
Solution Approach 1:
The patent implements dynamic gesture recognition that adapts to different navigation contexts. The system adjusts sensitivity thresholds and interpretation rules based on the current virtual environment state, allowing the same physical gesture to produce different navigation outcomes depending on context, thereby increasing versatility without proportionally increasing system complexity.
Data Source
AI summary
Various aspects of the subject technology relate to systems, methods, and machine-readable media for navigating through a shared artificial reality environment. Various aspects may include receiving an indication of a virtual object in the shared artificial reality environment. Aspects may also include receiving an input gesture indicative of a navigation command associated with the virtual object. Aspects may also include determining at least one type of the input gesture comprising flexion and extension, pronation and supination, or radial and ulnar. Aspects may also include determining a control method. Aspects may include determining a scrolling parameter. Aspects may include identifying the navigation command based on the type of the input gesture, the control method, and the scrolling parameter. Aspects may include applying the navigation command to the virtual object.