Dynamic Object Tracking in Augmented Reality
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Solution Overview
Problem
Object tracking in augmented reality systems becomes challenging when both the camera and the tracked object are moving, as it is difficult to distinguish between object motion and camera motion, leading to inaccurate tracking.
Innovation Solution
A method that involves acquiring earlier and later images from an image stream, identifying environment and object features, determining camera movement, estimating object features, and determining if the object has moved by comparing the number of matched features, with notifications displayed accordingly, allowing for accurate tracking of both camera and object poses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional object tracking is used when both camera and object are moving, then the system can maintain simple tracking algorithms, but the tracking accuracy deteriorates due to inability to distinguish object motion from camera motion
Solution Approach 1:
The patent segments the tracking problem into two independent components: camera pose tracking (using environment features) and object pose tracking (using object features). By separating these previously coupled tracking tasks, the system can accurately distinguish between camera motion and object motion, resolving the technical contradiction between tracking accuracy and algorithm complexity.
2Measurement precision
If the system switches to environment-based camera pose tracking to improve camera motion detection, then camera tracking accuracy improves, but the overall system complexity increases due to dual tracking mechanisms
Solution Approach 1:
The patent introduces environment features as an intermediary reference frame that mediates between the camera and the object. By tracking environment features to determine camera pose, and then using this camera pose information to track object features, the system creates a clear separation of tracking functions while maintaining overall system coherence through the intermediary environment reference.
Data Source
AI summary
A method of determining and displaying movement of an object in an environment using a moving camera includes identifying later environment features located in the environment in a later image, earlier environment features located in the environment in an earlier image, and earlier object features located on the object in the earlier image. The method further includes estimating object features in the later image using the earlier object features and a determined camera movement. The method further includes locating, in the later image, matched object features that are actual object features in the later image at a same location as the estimated object features. The method further includes determining that the object has moved between the earlier image and the later image if a number of matched object features does not exceed a threshold.