HMD Tracking via Camera and Optical Flow Mapping
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Solution Overview
Problem
Current virtual reality systems, particularly head-mountable displays (HMDs), face challenges in accurately tracking user movements and maintaining a seamless virtual environment experience due to limitations in detecting the relative position and orientation of HMDs within virtual or augmented reality spaces, which affects the immersion and interaction with the virtual environment.
Innovation Solution
The implementation of a data processing device and method that utilizes a combination of camera-based motion sensing and optical flow detection, along with hardware motion detectors, to track the HMD's movement and adjust the displayed images accordingly, ensuring that the virtual environment aligns with the user's head movements, and uses a mapping process to determine the relative positions of devices within the system for synchronized interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If camera-based motion sensing and optical flow detection are used to track HMD movements, then measurement precision of head position and orientation is improved, but device complexity increases due to multiple sensors and processing requirements
Solution Approach 1:
The system divides the tracking function into multiple independent components: camera-based motion sensing for positional tracking, optical flow detection for rotational tracking, and hardware motion detectors for acceleration data. Each component operates independently and contributes specific data to the overall tracking system, allowing for modular optimization and reduced individual component complexity.
Solution Approach 2:
The patent combines multiple detection methods (camera-based motion sensing, optical flow detection, and hardware motion detectors) into a unified tracking system. By merging these different sensing approaches, the system achieves comprehensive head position and orientation tracking that leverages the strengths of each method while compensating for their individual limitations.
2Reliability
If multiple detection methods are combined to track head movements accurately, then reliability of virtual environment alignment is improved, but loss of processing time increases due to multiple data streams requiring integration
Solution Approach 1:
The system performs preliminary processing of data from each sensor type independently before integration. Each detection method pre-processes its data stream to extract relevant features and convert raw data into standardized formats, reducing the computational burden during real-time integration and minimizing processing delays.
Solution Approach 2:
The system implements feedback mechanisms where the integrated tracking data is continuously monitored and used to adjust the processing parameters of individual sensors. This feedback loop optimizes the balance between processing time and alignment accuracy by dynamically adjusting sensor sampling rates and processing intensity based on current system performance and user activity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enhances the user's immersion by accurately tracking head movements and maintaining a consistent virtual environment, improving the overall interaction and experience in virtual and augmented reality applications by ensuring that the virtual environment dynamically adjusts to the user's position and orientation, thereby providing a more immersive and interactive experience.
Implementation Method 1
a camera to capture successive images of an optically detectable indicator of a second data processing device
Implementation Method 2
a motion detector to detect motion of the data processing device
Data Source
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AI summary
A data processing device comprises a camera to capture successive images of an optically detectable indicator of a second data processing device; a location detector configured to detect a location of the data processing device; a data receiver to receive location information from the second data processing device; and a processor to detect a mapping between the image location, in images captured by the camera, of the optically detectable indicator of the second data processing device, the communicated location of the second data processing device and the detected location of the data processing device.