3D User Interface Cursor Control via Coordinate Transformation
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Solution Overview
Problem
Existing three-dimensional (3D) user interfaces face challenges in accurately interpreting gestures due to misalignment between the fixed coordinate system of 3D sensors and the subjective coordinate system of users, leading to difficulties in identifying gestures and providing tactile feedback.
Innovation Solution
The method involves transforming 3D coordinates from a fixed sensor coordinate system to a subjective user coordinate system, using techniques such as vertical tilt correction, horizontal angle correction, spherical deformation, automatic learning, and manual calibration, to accurately interpret user gestures and provide visual and audio feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D coordinates are transformed from fixed sensor coordinate system to subjective user coordinate system, then gesture interpretation accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing transformation parameters (rotation matrices, translation vectors) that map between the fixed sensor coordinate system and the subjective user coordinate system. These pre-computed transformation data are then applied during gesture recognition to improve accuracy without performing complex real-time calculations, thus resolving the contradiction between measurement precision and device complexity.
2Measurement precision
If coordinate system alignment techniques are implemented, then gesture recognition accuracy is improved, but processing time increases
Solution Approach 1:
The system performs coordinate transformation parameter calculations in advance during system initialization or calibration phases, storing these transformation data for rapid application during actual gesture recognition. This preliminary computation approach maintains high gesture recognition accuracy while minimizing processing time during interactive operations.
Solution Approach 2:
The patent implements dynamic adjustment of coordinate transformation based on detected user position and orientation. The system adapts transformation parameters in real-time according to user movement, optimizing the balance between accuracy and processing efficiency by applying transformations only when and where needed during gesture recognition.
3Reliability
If multiple correction techniques (vertical tilt, horizontal angle, spherical deformation) are applied, then gesture interpretation fidelity is improved, but system complexity increases
Solution Approach 1:
The patent segments the coordinate transformation process into distinct correction stages: vertical tilt correction, horizontal angle correction, and spherical deformation correction. Each correction technique addresses a specific aspect of coordinate misalignment independently, allowing the system to apply only the necessary corrections for each gesture type, thereby improving fidelity while managing system complexity through modular processing.
Data Source
AI summary
A method, including receiving, by a computer executing a non-tactile three dimensional (3D) user interface, a first set of multiple 3D coordinates representing a gesture performed by a user positioned within a field of view of a sensing device coupled to the computer, the first set of 3D coordinates comprising multiple points in a fixed 3D coordinate system local to the sensing device. The first set of multiple 3D coordinates are transformed to a second set of corresponding multiple 3D coordinates in a subjective 3D coordinate system local to the user.