Rolling-Shutter Visual-Inertial Tracking for Eyewear Pose Accuracy
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Solution Overview
Problem
Rolling shutter cameras capture images with artifacts due to relative movement between the camera and scene, affecting the accuracy of visual-inertial tracking.
Innovation Solution
Adjust the number of poses calculated based on the movement of the eyewear device to conserve processing resources while maintaining acceptable augmented reality results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of poses calculated is increased to improve tracking accuracy, then measurement precision improves, but use of energy increases
Solution Approach 1:
The patent applies partial action by calculating poses selectively rather than computing all possible poses. The system determines poses for specific lines of the rolling shutter camera based on image artifacts, rather than calculating poses for the entire image uniformly. This reduces processing resources while maintaining tracking accuracy where artifacts indicate motion.
Solution Approach 2:
The patent applies local quality by treating different regions of the image differently based on artifact presence. Lines with artifacts receive pose calculations while lines without artifacts do not. This localized approach concentrates processing resources on areas that actually contribute to tracking accuracy improvement.
2Use of energy by moving object
If pose calculation is optimized to conserve processing resources, then use of energy decreases, but measurement precision deteriorates
Solution Approach 1:
The patent uses feedback from image artifacts to guide pose calculation decisions. The system analyzes the captured image for artifacts, and this feedback determines which lines require pose calculations. This feedback mechanism ensures that pose calculations are performed only when and where they are needed to maintain tracking accuracy, avoiding unnecessary computations.
Solution Approach 2:
The system uses the image data itself to determine where processing is needed. The artifacts present in the image self-identify the regions that require pose calculation, eliminating the need for external guidance or uniform processing across the entire image. The image serves its own analysis function.
3Speed
If rolling shutter camera captures image with relative movement, then speed of capture improves, but manufacturing precision deteriorates due to artifacts
Solution Approach 1:
The patent converts the harmful effect of motion artifacts into a beneficial signal for tracking. Rather than treating artifacts as errors to be eliminated, the system uses them as indicators of motion that provide valuable information for calculating accurate poses. The artifacts become a source of tracking data that improves overall system performance.
Solution Approach 2:
The patent changes the interpretation of image parameters by treating artifacts not as noise but as meaningful data. The system alters how image characteristics are used, transforming the artifact presence from a quality degradation into a useful parameter for pose determination and motion tracking.
Data Source
AI summary
Visual-inertial tracking of an eyewear device using a rolling shutter camera(s). The device includes a position determining system. Visual-inertial tracking is implemented by sensing motion of the device. An initial pose is obtained for a rolling shutter camera and an image of an environment is captured. The image includes feature points captured at a particular capture time. A number of poses for the rolling shutter camera is computed based on the initial pose and sensed movement of the device. The number of computed poses is responsive to the sensed movement of the mobile device. A computed pose is selected for each feature point in the image by matching the particular capture time for the feature point to the particular computed time for the computed pose. The position of the mobile device is determined within the environment using the feature points and the selected computed poses for the feature points.