HMD Calibration via Vehicle and User Motion Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Head-Mounted Display (HMD) devices face challenges in maintaining an optimal field-of-view during vehicle movements, leading to inadequate user experiences due to misalignment of VR content caused by vehicle and user movements, which existing technologies fail to adequately address.
Innovation Solution
A method and system for automatically calibrating HMD devices by detecting user and vehicle movements, determining calibration criteria, and dynamically adjusting sensor data to maintain a stable field-of-view, switching to non-immersive mode when criteria are not met, using a calibration unit and processor to manage sensor data from yaw, pitch, and roll axes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If the HMD device performs dynamic calibration based on user and vehicle movements, then the field-of-view stability is improved, but the device complexity increases
Solution Approach 1:
The HMD device performs self-calibration by automatically detecting user head movements and vehicle movements through integrated sensors, then adjusting its own sensor data without requiring external calibration equipment or manual intervention. The calibration unit uses the device's existing sensors to detect movements and dynamically adjust calibration parameters, making the system self-sufficient.
Solution Approach 2:
The system dynamically changes calibration parameters based on detected movements. The calibration unit modifies sensor data parameters in real-time by comparing initial calibration data with current sensor readings, adjusting the field-of-view parameters according to the detected user and vehicle movements to maintain stability.
2Measurement precision
If the HMD device performs frequent calibration, then the field-of-view accuracy is improved, but the user experience deteriorates due to disruptions
Solution Approach 1:
The calibration process is made dynamic rather than static. Instead of fixed periodic calibration, the system continuously monitors movement criteria and performs calibration only when movements exceed predefined thresholds. This dynamic approach allows the system to adapt to actual usage conditions, calibrating when necessary for accuracy while remaining passive during normal use to maintain user experience.
Solution Approach 2:
The system applies partial calibration action by using movement criteria thresholds to determine when calibration is necessary. Not all movements trigger calibration - only those exceeding predefined thresholds. This selective approach avoids unnecessary calibrations that would disrupt users while still performing calibration when it would improve accuracy.
3Measurement precision
If the HMD device uses multiple calibration criteria, then the calibration accuracy is improved, but the processing time increases
Solution Approach 1:
The system performs preliminary setup by establishing movement criteria thresholds before actual calibration occurs. These predefined thresholds for user movement and vehicle movement are set in advance, allowing the calibration unit to quickly compare current movements against established criteria without needing to calculate complex parameters in real-time, thus reducing processing time while maintaining accuracy.
4Speed
If the HMD device continuously monitors movements, then the calibration responsiveness is improved, but the energy consumption increases
Solution Approach 1:
The monitoring operates periodically rather than continuously. The calibration unit checks movements at intervals defined by the movement criteria thresholds, activating full calibration processing only when thresholds are exceeded. During normal operation between threshold events, the system maintains minimal monitoring with reduced processing, thus improving responsiveness when needed while conserving energy during stable periods.
Data Source
AI summary
The proposed invention provides a method for calibrating a HMD device of a user in a vehicle. The method includes detecting user movements while viewing VR content in the vehicle and checking if these motions meet user movement criteria. The method also includes detecting if the vehicle is stationary or moving. Further, on detecting that the vehicle is stationary dynamically calibrating the HMD device based on the movements of the user and on detecting that the vehicle is in motion dynamically calibrating the HMD device based on vehicle movements and the movements of the user.