Magic Leap, Inc.

Mohamed Souiai

Ankur Gupta

Igor Napolskikh

Moshe Bouhnik

Yu-Hsiang Huang

Etienne Gregoire Grossman

Techniques for addressing deformations in a virtual or augmented headset described. In some implementations, cameras in a headset can obtain image data at different times as the headset moves through a series of poses of the headset. One or more miscalibration conditions for the headset that have occurred as the headset moved through the series of poses can be detected. The series of poses can be divided into groups of poses based on the one or more miscalibration conditions, and bundle adjustment for the groups of poses can be performed using a separate set of camera calibration data. The bundle adjustment for the poses in each group is performed using a same set of calibration data for the group. The camera calibration data for each group is estimated jointly with bundle adjustment estimation for the poses in the group.

Calibration for virtual or augmented reality systems

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for calibrating an augmented reality device using camera and inertial measurement unit data. In some implementations, a bundle adjustment process jointly optimizes or estimates states of the augmented reality device. The process can use, as input, visual and inertial measurements as well as factory-calibrated sensor extrinsic parameters. The process performs bundle adjustment and uses non-linear optimization of estimated states constrained by the measurements and the factory calibrated extrinsic parameters. The process can jointly optimize inertial constraints, IMU calibration, and camera calibrations. Output of the process can include most likely estimated states, such as data for a 3D map of an environment, a trajectory of the device, and/or updated extrinsic parameters of the visual and inertial sensors (e.g., cameras and IMUs).

Joint camera and inertial measurement unit calibration

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using depth data to update camera calibration data. In some implementations, a frame of data is captured including (i) depth data from a depth sensor of a device, and (ii) image data from a camera of the device. Selected points from the depth data are transformed, using camera calibration data for the camera, to a three-dimensional space that is based on the image data. The transformed points are projected onto the two-dimensional image data from the camera. Updated camera calibration data is generated based on differences between (i) the locations of the projected points and (ii) locations that features representing the selected points appear in the two-dimensional image data from the camera. The updated camera calibration data can be used in a simultaneous localization and mapping process.

Camera calibration using depth sensor data

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for camera calibration during bundle adjustment. One of the methods includes maintaining a three-dimensional model of an environment and a plurality of image data clusters that each include data generated from images captured by two or more cameras included in a device. The method includes jointly determining, for a three-dimensional point represented by an image data cluster (i) the newly estimated coordinates for the three-dimensional point for an update to the three-dimensional model or a trajectory of the device, and (ii) the newly estimated calibration data that represents the spatial relationship between the two or more cameras.

Growing community of inventors

Plantation, FL, United States of America

Mohamed Souiai