HMD Avatar Motion Synchronization via Segmented Sensor Tracking
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Solution Overview
Problem
Current virtual reality systems lack seamless integration of user motion and visual field coordination across multiple users, leading to inconsistencies and reduced immersion in shared virtual spaces.
Innovation Solution
A head-mounted device (HMD) system that uses a combination of sensors and cameras to track user motion and visual focus, synchronizing the virtual camera's position and orientation with the user's head movements, and generating a synchronized field-of-view image for multiple users, allowing for precise coordination of avatars and environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion tracking sensors are used to detect user movement, then avatar motion accuracy is improved, but device complexity increases
Solution Approach 1:
The system divides motion tracking into two independent segments: IMU sensors mounted on the HMD for head motion detection, and separate motion capture cameras for body motion detection. This segmentation allows each subsystem to specialize in specific motion types, improving overall measurement precision while managing device complexity through modular architecture.
Solution Approach 2:
The patent introduces an intermediary synchronization mechanism that coordinates data from multiple sensors (IMU, motion capture cameras, eye tracking cameras) and integrates them into a unified avatar control system. This intermediary layer harmonizes data from different sources, maintaining high measurement accuracy while managing the complexity of multi-sensor integration.
2Reliability
If multiple sensors and cameras are integrated for comprehensive tracking, then coordination accuracy between users is improved, but device complexity increases
Solution Approach 1:
The system segments tracking functions across multiple devices: HMDs worn by users for head and eye tracking, and separate motion capture cameras for body motion. This segmentation distributes system complexity across multiple simpler components while achieving high coordination accuracy through their integrated operation.
Solution Approach 2:
The HMD system performs multiple functions simultaneously: head position tracking, eye gaze detection, and visual field rendering. This multi-functionality consolidates what would otherwise require separate devices, improving coordination accuracy while managing overall system complexity through unified hardware design.
3Adaptability or versatility
If visual field rendering is synchronized with head movement, then user immersion is improved, but processing requirements increase
Solution Approach 1:
The system pre-calculates and buffers visual field images based on predicted head motion trajectories. By preparing rendering data in advance and using predictive algorithms for head movement, the system reduces real-time processing requirements while maintaining high visual field coordination accuracy for immersive experience.
Solution Approach 2:
The visual field rendering is updated at optimized periodic intervals synchronized with natural head movement frequencies. This periodic rendering approach, combined with motion prediction, reduces the processing power required compared to continuous high-frequency rendering, while maintaining visual field coordination quality.
Data Source
AI summary
A method includes defining a virtual space including includes a first avatar object associated with a first user. The first avatar object includes a first part and a second part. The method includes moving the first avatar object in response to a first input from the first user. The first input includes a first motion information for identifying a motion of a part of a body of the first user, and the first part of the first avatar object is moved in accordance with the first motion information. The method includes acquiring supplementary information, independent of a detected movement of the first user, for defining a motion of the second part. The method includes moving the second part based on the supplementary information. The method includes identifying a visual field in the virtual space of a second user different from the first user. The method includes generating a visual-field image.