Magic Leap, Inc.

Ares Trading S.a.

Daniel E Koppel

Ashwin Swaminathan

Frank Thomas Steinbruecker

Lipu Zhou

Yan Zhou

Lei Tan

Martin T Chian

Vinayram Balakumar

Hui Ju

Konstantinos Zampogiannis

Pooja Piyush Mehta

A method of efficiently and accurately computing a pose of an image with respect to other image information. The image may be acquired with a camera on a portable device and the other information may be a map, such that the computation of pose localizes the device relative to the map. Such a technique may be applied in a cross reality system to enable devices to efficiently and accurately access previously persisted maps. Localizing with respect to a map may enable multiple cross reality devices to render virtual content at locations specified in relation to those maps, providing an enhanced experience for uses of the system. The method may be used in other devices and for other purposes, such as for navigation of autonomous vehicles.

Efficient localization based on multiple feature types

Methods and apparatus for providing a representation of an environment, for example, in an XR system, and any suitable computer vision and robotics applications. A representation of an environment may include one or more planar features. The representation of the environment may be provided by jointly optimizing plane parameters of the planar features and sensor poses that the planar features are observed at. The joint optimization may be based on a reduced matrix and a reduced residual vector in lieu of the Jacobian matrix and the original residual vector.

Computationally efficient method for computing a composite representation of a 3D environment

Systems and methods for automated imaging and evaluation of image based features are disclosed herein. Method for automated imaging and evaluation of image based features can include receiving time-lapse images of at least one human embryo contained in a multi-well culture dish that can have a plurality of micro-wells. Image based features can be automatically generated from the time-lapse images of the human embryo. The image based features, which can include a cavitation feature, can be inputted into a classifier. The classifier can automatically and directly generate a viability prediction with the classifier from the image-based features.

Systems and methods for automated assessment of embryo quality using image based features

Systems and methods for generating a mask for automated assessment of embryo quality are disclosed herein. The method for generating a mask for automated assessment of embryo quality can include receiving an image, including a plurality of pixels, of a human embryo from an imaging system. A pixel can be selected and features of the selected pixel can be determined by generating a plurality of random boxes of random sizes and at random locations about the selected pixel. The selected pixel can be identified as one of: inside of a mask area; and outside of the mask area based on the determined features.

Systems and methods for generating a mask for automated assessment of embryo quality

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San Jose, CA, United States of America

Daniel E Koppel