Virtual Reality Avatar Eye Movement Simulation
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Solution Overview
Problem
Current virtual reality systems struggle to present eye movements and eye contact effectively, especially when user devices lack eye tracking capabilities, impacting social interactions in virtual worlds.
Innovation Solution
A computer-based eye movement model is used to animate eye movements for avatars, employing machine learning to simulate natural eye patterns based on real-world interactions, which can be personalized and triggered by context or user inputs, allowing for realistic eye contact without requiring eye tracking devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If eye tracking sensors are used to capture real eye movements, then the realism of eye contact is improved, but the device complexity and cost increase
Solution Approach 1:
The patent creates a virtual copy of eye movement behavior through machine learning models that simulate natural eye patterns. Instead of requiring physical eye tracking sensors, the system generates synthetic eye movement data that replicates realistic gaze behavior, thereby achieving realistic eye contact without the complexity of hardware eye trackers.
Solution Approach 2:
The system enables avatars to generate their own eye movements autonomously through pre-trained machine learning models. The eye movement generation is self-contained within the software architecture, eliminating the need for external eye tracking devices and reducing overall system complexity while maintaining realism.
2Measurement precision
If eye tracking capabilities are required for all user devices, then the accuracy of eye movement presentation is improved, but the adaptability to different devices decreases
Solution Approach 1:
The patent develops a universal eye movement generation system that works across all device types without requiring eye tracking hardware. The machine learning models are designed to be device-agnostic, generating realistic eye movements through software alone, thereby achieving both accuracy and broad device compatibility simultaneously.
Solution Approach 2:
The system introduces an intermediary layer of machine learning-based virtual eye movement generation between the user input and the avatar representation. This intermediary enables accurate eye movement presentation on devices without eye trackers by synthesizing realistic gaze patterns from alternative input sources such as head tracking or direct manipulation.
3Ease of operation
If virtual eye movements are generated without eye tracking data, then the device requirements are simplified, but the naturalness of eye movement patterns may deteriorate
Solution Approach 1:
The patent employs pre-trained machine learning models that have been trained in advance on large datasets of real eye movement recordings. This preliminary training captures natural eye movement patterns, allowing the system to generate realistic virtual eye movements without requiring real-time eye tracking data, thus maintaining naturalness while simplifying device requirements.
Solution Approach 2:
The system adjusts and optimizes parameters of the virtual eye movement generation to match empirical characteristics of natural eye behavior. By tuning parameters such as fixation duration, saccade amplitude, and gaze transition timing based on psychological and physiological principles, the system achieves natural-looking eye movements without eye tracking hardware.
Data Source
AI summary
A computing system and method to implement a three-dimensional virtual reality world with avatar eye movements without user eye tracking. A position and orientation of a respective avatar in the virtual reality world is tracked to generate a view of the virtual world for the avatar and to present the avatar to others. In response to detecting a predetermined event, the computing system predicts a point (e.g., the eye of another avatar) that is of interest to the respective avatar responsive to the event, and computes, according to an eye movement model, an animation of the eyes of the respective avatar where the gaze of the avatar moves from an initial point to the predicted point and/or its vicinity for a period of time and back to the initial point.