XR Viewfinder Switching Between Hand and Head Tracking
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Solution Overview
Problem
Implementing an interface for head-wearable devices that allows users to accurately capture and query specific real-world objects in an XR environment is challenging due to the lack of precise control over framing and the need for user interaction mechanisms that are unfamiliar to users.
Innovation Solution
The interface provides two mechanisms: a hand-tracked viewfinder, where users move a viewfinder over objects with a pinching motion, and a head-tracked viewfinder, which automatically frames objects with a verbal command, allowing users to snap objects with visual feedback, and a hybrid approach combining both.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a hand-tracked viewfinder is used for object capture, then user control and precision are improved, but device complexity and learning curve increase
Solution Approach 1:
The system dynamically switches between hand-tracking mode and head-tracking mode based on user needs and environmental context. The hand-tracked viewfinder is activated when users need precise control, while the head-tracked viewfinder is used for simpler hands-free operation, making the interface adaptive rather than static.
Solution Approach 2:
The object capture functionality is segmented into two distinct modes: hand-tracking mode for precision control and head-tracking mode for simplicity. This segmentation allows users to choose the appropriate level of complexity based on the task at hand, reducing the perceived complexity while maintaining precision when needed.
2Ease of operation
If a head-tracked viewfinder is used for automatic framing, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The system dynamically adjusts the level of automation in framing based on the selected mode. In head-tracking mode, automatic framing provides ease of operation for casual use. In hand-tracking mode, the system transitions to manual framing control, allowing users to precisely position the viewfinder frame around their desired object, thereby improving measurement precision when needed.
Solution Approach 2:
The head-tracked viewfinder automatically frames objects based on head orientation and gaze direction, allowing the system to self-adjust the frame position without manual intervention. This self-service capability simplifies operation for users who do not require precise control.
3Ease of operation
If visual feedback is provided during object capture, then user control is improved, but device complexity increases
Solution Approach 1:
The system provides real-time visual feedback by displaying the viewfinder frame overlaid on the camera view, showing users exactly what will be captured. This feedback mechanism helps users understand the relationship between their head or hand movements and the resulting frame position, improving control without requiring complex additional hardware.
Data Source
AI summary
In an example, two different mechanisms for specifying a real-world object visible in a view are provided. Each of these different mechanisms has their own benefits, and indeed in another example a hybrid of the two mechanisms may be used, where a user can seamlessly switch between mechanisms based on their own desires or scenarios.