Extended Reality Interaction Point Determination via Hand Vector Alignment
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Solution Overview
Problem
Existing extended reality systems face challenges in achieving precise interaction between users and target objects, leading to discomfort and inefficiency in user experience.
Innovation Solution
A method and device that generate a point cloud based on view vectors, a hand bubble based on hand point and angle, and an approximate sphere to determine a final interaction point, enhancing interaction precision by using a hand vector aligned with the object's normal vector.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a simple interaction point determination method is used, then the device complexity is reduced, but the interaction precision deteriorates
Solution Approach 1:
The interaction determination process is divided into distinct modules: a first module generating a point cloud of the target object based on multiple view vectors, a second module generating a hand bubble based on hand point and hand point angle, and a third module generating an approximate sphere and determining the final interaction point. This segmentation allows each module to focus on a specific aspect of the interaction determination, improving overall precision while managing complexity through modular design.
Solution Approach 2:
The patent introduces intermediate geometric constructs (hand bubble, approximate sphere, hand vector) that serve as mediators between the raw hand tracking data and the final interaction point determination. These intermediaries refine the interaction calculation by providing structured representations of hand position and orientation, thereby improving precision without requiring direct complex calculations between all system components.
2Measurement precision
If the hand point angle is kept fixed, then the device complexity is reduced, but the interaction precision deteriorates
Solution Approach 1:
The hand point angle is made dynamic rather than fixed. The third module adjusts the hand point angle based on the generated approximate sphere and hand vector to optimize the interaction point determination. This dynamic adjustment allows the system to adapt to different interaction scenarios and improve precision while the modular architecture manages the resulting complexity.
3Measurement precision
If a single view vector is used, then the device complexity is reduced, but the measurement precision of the target object deteriorates
Solution Approach 1:
The target object representation is segmented into multiple point clouds, each generated from different view vectors. The first module creates a comprehensive point cloud by combining information from multiple viewing angles, which improves the accuracy and completeness of the target object representation while the modular structure manages the computational complexity.
Data Source
AI summary
A device includes a first module configured to generate a point cloud of a target object based on a plurality of view vectors, a second module configured to generate a hand bubble based on a hand point and a hand point angle and a third module configured to generate an approximate sphere based on the point cloud and the hand bubble, and to determine a final interaction point of the target object based on the approximate sphere and a hand vector.