Co-Located HMD Pose Tracking Without Markers or External Cameras
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Solution Overview
Problem
Conventional artificial reality systems require markers or external cameras to determine body position, which is cumbersome, time-consuming, and adds complexity and expense.
Innovation Solution
A pose tracking system that uses HMDs to track pose and body positioning without markers or external cameras, allowing HMDs to receive and refine pose and body position information from other HMDs within the same environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If markers or external cameras are used to determine body position, then measurement precision is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The patent removes external markers and separate camera systems from the artificial reality environment, extracting only the essential tracking functionality and integrating it directly into the HMD. This eliminates the complex external infrastructure while maintaining pose estimation capability through onboard sensors and computational methods.
Solution Approach 2:
The HMD is designed to perform multiple functions: display artificial reality content, capture user pose information through integrated sensors, and communicate this data to other HMDs. This multi-functionality eliminates the need for separate external cameras and markers, reducing overall system complexity while maintaining tracking precision.
2Measurement precision
If markers or external cameras are used to determine body position, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
By removing the requirement for physical markers and external camera installations, the system dramatically simplifies setup. Users simply need to wear the HMD, and the onboard sensors automatically begin tracking pose information without requiring additional configuration or calibration equipment.
Solution Approach 2:
The HMD autonomously performs pose estimation using its integrated sensors and communicates this information to other HMDs in the environment. The system self-configures and begins operation immediately upon activation, eliminating the need for manual marker placement or external camera setup by users.
3Measurement precision
If external cameras or sensors are added to determine pose, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent merges the pose estimation functionality directly into the HMD by integrating sensors and computational algorithms within the head-mounted device itself. This consolidation eliminates the need for separate external cameras and sensors, reducing the total number of components while maintaining accurate pose tracking through the combined onboard systems.
4Measurement precision
If HMDs share pose information from multiple sources, then measurement precision is improved, but device complexity increases
Solution Approach 1:
HMDs continuously exchange pose estimation data with other HMDs in the environment, creating a feedback loop where each device refines its own pose information using data from multiple sources. This collaborative feedback mechanism improves measurement precision while distributing the computational load across all devices rather than requiring any single HMD to process all information independently.
Data Source
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AI summary
Artificial reality (AR) systems track pose and skeletal positioning for multiple co-located participants, each having a head mounted display (HMD). Participants can join a shared artificial reality event or experience with others in the same location. Each participant's HMD can independently render AR content for the participant based on the participant's pose and pose information obtained from other participants' HMDs. A participating HMD may broadcast tracking estimates for skeletal points of interest (e.g., joints, finger tips, knees, ankle points, etc.) that are within the field-of-view of the HMD's cameras and/or sensors. A participating HMD may receive skeletal position information determined by other HMDs, and aggregate the received tracking information along with internal tracking information to construct an accurate, full estimate of its own pose and skeletal positioning information for its corresponding participant.