FIELD

This disclosure relates to systems and methods for computer vision (CV) and augmented reality (AR). More specifically, to systems and methods for positioning computer-generated augmented reality content with improved precision and accuracy across devices and platforms.

SUMMARY

The present disclosure provides systems, apparatuses, and methods relating to computer vision and augmented reality.

In some embodiments, a computer-implemented method for transforming between a native coordinate space and a reference coordinate space may include: recognizing, using a sensor and a native computer vision (CV) system of a mobile digital device (MDD), a local point cloud corresponding to a real-world trackable feature; and determining a transform between the local point cloud and a reference point cloud corresponding to the real-world trackable feature, based at least in part on a position and orientation of the MDD relative to the reference point cloud, the position and orientation being determined by the sensor and a secondary CV system of the MDD; wherein determining the transform between the local point cloud and the reference point cloud includes using processing logic to execute a constrained bundle adjustment (BA) method to optimize the transform, wherein the constrained BA method comprises minimizing an error function, the error function including reprojection error and a measure of differences between native and transformed sensor positions.

In some embodiments, a system for transforming between a native coordinate space and a reference coordinate space may include: a mobile digital device (MDD) including: a sensor; and processing logic configured to: recognize a local point cloud corresponding to a real-world trackable feature using the sensor and a native computer vision (CV) system of the MDD; and determine a transform between the local point cloud and a reference point cloud corresponding to the real-world trackable feature, based at least in part on a position and orientation of the MDD relative to the reference point cloud; wherein determining the transform between the local point cloud and the reference point cloud includes minimizing an error function including reprojection error and a measure of differences between native and transformed sensor positions.

In some embodiments, a computer-implemented method for transforming between a local coordinate system and a reference coordinate system may include: recognizing, using a sensor and a first computer vision (CV) system of a mobile digital device (MDD), a local point cloud corresponding to a real-world trackable feature; determining a position and an orientation of the MDD relative to a reference point cloud corresponding to the real-world trackable feature, using the sensor and a second CV system of the MDD; determining a transform between the local point cloud and the reference point cloud; and determining a position of an augmented reality (AR) content item relative to the local point cloud by applying the transform to AR positioning information defined relative to the reference point cloud.

Features, functions, and advantages may be achieved independently in various embodiments of the present disclosure, or may be combined in yet other embodiments, further details of which can be seen with reference to the following description and drawings.

