Augmented Reality Object Tracking with Displacement Feedback
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Solution Overview
Problem
Current augmented reality systems lack efficient methods for tracking and maintaining the precise positioning of objects within a field of view over time, which is crucial for ensuring continuity in content creation, such as film or virtual reality applications.
Innovation Solution
The system captures real-world objects, generates object data associating their positions at different times, determines displacement values, and modifies virtual objects to indicate changes, allowing for accurate tracking and rendering in an augmented reality environment, with options for displaying composite scenes and storing data for future reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If augmented reality systems use traditional object tracking methods, then the system complexity remains manageable, but the positioning precision and continuity maintenance deteriorate
Solution Approach 1:
The system segments object tracking into multiple independent components: capturing object data at different times, generating separate virtual objects for each time point, calculating displacement values, and rendering with different colors. This segmentation allows precise tracking through multiple data points while managing complexity by handling each segment independently through automated processing.
Solution Approach 2:
The system implements feedback by comparing object positions at different time points, calculating displacement values, and providing visual feedback through color-coded virtual objects. When displacement exceeds a threshold, the system highlights the object with a second color to indicate misplacement, enabling continuous correction and maintenance of positioning precision.
2Measurement precision
If the system captures and processes object data at multiple time points, then the tracking accuracy improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by capturing object data at multiple time points before final rendering, storing this data for later comparison. Virtual objects are generated in advance based on captured data, allowing the system to maintain high tracking accuracy through pre-processing rather than real-time computation during rendering.
Solution Approach 2:
The system creates virtual copies of real objects at different time points without requiring continuous processing of the original objects. These virtual objects store positional information and can be rendered independently, reducing processing time while maintaining tracking accuracy through comparison of the copied data sets.
3Stability of the object's composition
If the system provides real-time feedback on object displacement, then the continuity in content creation improves, but the computational load increases
Solution Approach 1:
The system applies local quality by providing different visual feedback for different objects based on their displacement characteristics. Objects with displacement within the threshold maintain their first color, while only objects exceeding the threshold receive special highlighting. This localized approach ensures continuity consistency for all objects while reducing computational load by processing only those requiring attention.
4Loss of information
If the system uses color changes to indicate displacement, then the visual feedback clarity improves, but the rendering complexity increases
Solution Approach 1:
The system uses color changes as a simple visual indicator of object displacement status. Virtual objects are rendered in a first color when displacement is within acceptable thresholds and switch to a second color when displacement exceeds the threshold. This straightforward color-coding system provides clear feedback without requiring complex rendering modifications or additional visual elements.
Data Source
AI summary
Systems and methods for tracking objects in a field of view are disclosed. In one embodiment a method may include capturing, via a camera, a real-world object in the field of view; generating a first object data associating the real-world object with a first position of the real-world object in a real-world environment at a first time; generating a virtual object representative of the real-world object depicting the real-world object in the first position at the first time; generating a second object data associating the real-world object with a second position of the real-world object in the real-world environment at a second time, determining a displacement value of the real-world object between the first position and the second position, modifying the virtual object to include an indication that the real-world object has been displaced when the displacement value is greater than a threshold value.