VR Sickness Prediction via Visual Copying and Image Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current VR technologies face challenges in predicting and monitoring VR sickness, such as motion sickness, due to inconsistencies between visual and sensory information, making it difficult to ensure user safety and provide effective content services.
Innovation Solution
An apparatus and method using machine learning based on supervised learning to analyze VR content, combining user inputs and sensor data to establish a correlation model between VR sickness-inducing factors and user experiences, allowing for real-time monitoring and prediction of VR sickness without the need for additional equipment or bio-signal detection sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional equipment and bio-signal detection sensors are used to monitor VR sickness, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent uses visual copying of bio-signal information through display images instead of direct sensor measurement. The system captures and processes visual information from the user's appearance (e.g., facial expressions, sweating) to infer VR sickness levels, creating a visual copy of physiological states without requiring complex bio-signal sensors.
Solution Approach 2:
The patent replaces mechanical/physical sensor-based detection systems with an image processing-based system. Instead of using accelerometers, gyroscopes, or electrodermal activity sensors, the system uses standard imaging devices to detect and analyze visual indicators of VR sickness, substituting a simpler optical system for complex mechanical sensing.
2Ease of operation
If subjective user opinions are collected through questionnaires, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent introduces an image processing system as an intermediary between the user's physiological state and the measurement system. Instead of directly asking users about their comfort levels (subjective) or using complex sensors (objective), the system uses visual indicators from images as an intermediary that objectively reflects the user's physical state while being easy to collect.
Solution Approach 2:
The patent substitutes subjective self-reporting mechanisms (questionnaires) with objective image-based detection. The system replaces the need for users to articulate their comfort levels with automatic visual analysis that detects physiological changes through imaging, transforming a subjective measurement problem into an objective one.
3Adaptability or versatility
If HMD devices are used for VR content delivery, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent makes the monitoring system universal by using standard imaging devices that can capture visual information regardless of the specific VR delivery method. The same image processing algorithm can analyze users experiencing VR through HMDs, screens, or other displays, making the system adaptable to multiple VR content delivery platforms without requiring VR-specific monitoring equipment.
Data Source
AI summary
Disclosed is an apparatus and method of monitoring a VR (Virtual Reality) sickness prediction model for virtual reality content. A method of monitoring a VR sickness prediction model according to the present disclosure includes: displaying the virtual reality content on a display unit; acquiring an user input; analyzing the virtual reality content on a basis of the acquired user input; and displaying an analysis result for the virtual reality content on the display unit.