Gaze Direction Determination Using Inverse Camera Transformation
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Solution Overview
Problem
Existing gaze tracking technologies face latency issues in dynamically updated 3D scenarios, leading to a poorer user experience and limited time-wise granularity for user interaction, particularly in dynamic game situations where the virtual camera's position and direction change quickly.
Innovation Solution
A method and system that determine the current gaze direction of a user by calculating a modified gaze direction based on the inverse of the time-dependent virtual camera 3D transformation, accounting for changes in the virtual camera's position and direction between sampling time points, to compensate for latency and improve user interaction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional gaze tracking is used in dynamically updated 3D scenes, then the system is simple to implement, but latency occurs during rapid camera movements causing poor user experience
Solution Approach 1:
The system performs preliminary transformation of gaze directions using predicted camera transformations before the actual camera update occurs. By pre-calculating where the gaze should point based on anticipated camera movements, the system eliminates latency delays and provides immediate responsive feedback to user interactions in dynamic 3D scenes.
Solution Approach 2:
Instead of transforming gaze directions forward with camera movements (which causes latency), the system applies inverse transformations to compensate for camera movements. By calculating the inverse of the camera's transformation matrix and applying it to the gaze direction, the system effectively 'undoes' the camera movement effect on the gaze pointer, maintaining accurate alignment with user intent despite rapid camera changes.
2Measurement precision
If gaze tracking compensates for rapid camera movements, then user interaction accuracy improves, but device complexity increases
Solution Approach 1:
The system uses a single transformation matrix that serves multiple purposes: it represents the camera's 3D transformation, enables prediction of future camera positions, and provides the inverse transformation for gaze compensation. This multi-functional approach maintains high measurement precision while avoiding the need for separate complex subsystems for each function.
Solution Approach 2:
The system continuously monitors camera transformation changes and dynamically adjusts gaze directions based on detected movements. By implementing a feedback loop that detects camera transformation updates and automatically compensates gaze pointers in real-time, the system achieves high interaction accuracy through a relatively simple adaptive mechanism rather than complex predictive models.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances user experience by providing a more fluent interaction with 3D scenes, even during rapid camera movements, by accurately estimating the user's gaze direction and reducing latency-related delays, thus improving the overall user interaction efficiency.
Implementation Method 1
This can be done, for example, by illuminating a region in which the eye is sought with infrared radiation
Implementation Method 2
light enters the eye and is reflected or absorbed and re-emitted through the pupil
Implementation Method 3
light enters the eye and is reflected or absorbed and re-emitted through the pupil
Implementation Method 4
capturing an image of the region; and detecting bright spots in the image
Data Source
AI summary
A method for determining a current gaze direction of a user in relation to a three-dimensional (“3D”) scene, the 3D scene sampled by a rendering function to produce a two-dimensional (“2D”) projection image of the 3D scene, the sampling performed based on a virtual camera in turn being associated with a camera position and camera direction in the 3D scene. The method includes determining, by a gaze direction detection means, a first gaze direction of the user related to the 3D scene at a first gaze time point. The method includes determining a time-dependent virtual camera 3D transformation representing a change of a virtual camera position and/or virtual camera direction between the first gaze time point and a second sampling. The method includes determining the current gaze direction as a modified gaze direction calculated based on the first gaze direction and an inverse of the time-dependent virtual camera 3D transformation.