Inside-Out HMD Tracking Using Vehicle Interior Edge Models
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Solution Overview
Problem
Current head-mounted displays (HMDs) for virtual reality (VR) and augmented reality (AR) are limited to static environments due to their reliance on outside-in tracking and hardware-dependent 6DOF algorithms, which cannot deactivate translation in dynamic environments.
Innovation Solution
A system that enables mobile HMDs to function in dynamic environments by incorporating an edge model of a vehicle's interior, allowing for computer-vision-based 6DOF tracking. This system corrects the HMD's position using the edge model, preventing incorrect tracking and enabling use during dynamic journeys.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If outside-in tracking with external sensors is used, then tracking accuracy is improved, but device complexity and portability are worsened
Solution Approach 1:
The patent extracts the tracking function from external sensors and relocates it to the HMD itself through inside-out tracking. The HMD's camera and processor capture and analyze environmental features directly, eliminating the need for external tracking sensors while maintaining tracking capability.
Solution Approach 2:
The HMD performs tracking autonomously using its own camera and onboard processing. The device captures images, identifies environmental features, calculates its position and orientation, and updates the virtual environment without requiring external tracking infrastructure, enabling portable standalone operation.
2Speed
If hardware-dependent 6DOF algorithms are implemented in firmware, then processing speed is improved, but adaptability to different environments is worsened
Solution Approach 1:
The patent implements a dynamic tracking system that adapts to different environments in real-time. The software-based 6DOF algorithm dynamically identifies and tracks relevant environmental features based on current camera input, allowing the system to adjust to varying lighting conditions, textures, and spatial configurations without requiring hardware changes.
Solution Approach 2:
The system changes processing parameters dynamically based on environmental conditions. The software algorithm adjusts feature detection thresholds, tracking update rates, and algorithmic parameters according to the specific environment being tracked, enabling adaptability while maintaining efficient processing through optimized firmware execution.
3Device complexity
If inside-out tracking is used without external trackers, then device complexity is reduced, but tracking reliability in dynamic environments is worsened
Solution Approach 1:
The HMD's camera serves multiple functions: it captures display content for the user and simultaneously captures environmental features for tracking. This multi-functionality enables inside-out tracking without additional dedicated sensors, reducing device complexity while maintaining reliable tracking through sophisticated software processing of the camera's dual-purpose data.
Data Source
AI summary
When at least one mobile head-mounted display (HMD) is located in at least one vehicle, a control unit of the HMD performs inside-out tracking based on a six-degree-of-freedom (6DOF) algorithm with the aid of at least one camera image captured by at least one camera, using a 6DOF-algorithm-based translation of the at least one mobile HMD. The HMD control unit executes an application that creates an edge model of an interior of the vehicle and provides automated computer-vision-based 6DOF tracking of the at least one mobile HMD.