Tracking Mode Transition for Mixed Reality Object Interaction
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Solution Overview
Problem
Conventional artificial reality systems face difficulties in efficiently transitioning between tracking methods for real-world objects, leading to inefficiencies in user interaction and obstructed visual feedback, particularly with head-worn display systems that obstruct the line of sight to real-world objects.
Innovation Solution
The system implements a method to track primary and secondary real-world objects using different tracking methods (e.g., computer vision, optical, inertial) and transitions between these methods based on detected interactions, allowing for seamless representation of real-world objects in an artificial environment and optimizing tracking efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If head-worn display systems are used to provide immersive artificial reality experiences, then user immersion and engagement are improved, but visual feedback and line of sight to real-world objects are obstructed
Solution Approach 1:
The system introduces virtual representations of real-world objects as an intermediary between the user and actual objects. These virtual proxies provide visual feedback about real-world object positions and states without requiring the user to remove the head-worn display or break immersion, thus mediating the information loss caused by the display obstruction
Solution Approach 2:
The system implements a feedback mechanism where real-world objects are tracked and their positions are continuously reflected in the artificial reality environment through virtual representations. This provides users with visual feedback about the physical environment while maintaining immersion, allowing them to locate and interact with real-world objects like game controllers without removing the display
2Reliability
If multiple tracking methods are employed to monitor real-world objects, then tracking accuracy and reliability are improved, but system complexity and computational requirements increase
Solution Approach 1:
The system dynamically transitions between different tracking methods based on the operational context. When a user interacts with a real-world object, the system switches from inertial tracking to computer vision tracking, optimizing accuracy only when needed. This dynamic adaptation maintains reliability while reducing overall system complexity and computational burden during non-interaction periods
Solution Approach 2:
The system changes the tracking parameter state by switching between different tracking methodologies (inertial vs. computer vision) depending on the situation. This parameter change allows the system to maintain high tracking accuracy during critical interaction moments while operating in a lower-complexity mode during normal operation, effectively managing the trade-off between reliability and complexity
3Measurement precision
If computer vision tracking is used to monitor real-world objects, then tracking accuracy during interaction is improved, but power consumption and processing requirements increase
Solution Approach 1:
The system uses periodic action by switching between inertial tracking (low power) and computer vision tracking (high precision but high power) based on interaction detection. Computer vision tracking is activated periodically only when interaction events are detected, rather than running continuously, thus achieving high precision when needed while minimizing overall power consumption during non-interaction periods
Data Source
AI summary
The disclosed computer-implemented method may include tracking (1) a position of a primary real-world object within a real-world environment via a primary tracking method, and (2) a position of a secondary real-world object within the real-world environment via a secondary tracking method. The method may further include presenting (1) a primary virtual object at a position within an artificial environment corresponding to the tracked position of the primary real-world object, and (2) a secondary virtual object at a position within the artificial environment corresponding to the tracked position of the secondary real-world object. The method may further include (1) detecting an interaction of the primary real-world object with the secondary real-world object, and (2) transitioning to tracking the position of the primary real-world object via the secondary tracking method. Various other methods, systems, and computer-readable media are also disclosed.