Daqri, LLC

Facebook Technologies, LLC

Jakob Zillner

Daniel Wagner

Luca Ricci

Jeroen Diederik Hol

Brian Mullins

Branislav Micusik

William Hoff

Daniel Wolf

Systems and methods for generating composite depth images are disclosed. Exemplary implementations may: capture, by a depth sensor, a set of depth images over a capture period of time; generate, by an inertial sensor, inertial signals that convey values of one or more inertial parameters characterizing motion of the depth sensor during the capture period of time; select a target capture position based on one or more of the capture positions of the set of depth images; generate, using the values of the one or more inertial parameters during the capture period of time, re-projected depth images; and generate a composite depth image by combining multiple depth images, such multiple depth images including a first re-projected depth image and a second re-projected depth image.

Systems and methods for generating composite depth images based on signals from an inertial sensor

A system and method for offloading object detection are described. A server receives first sensor data from a first sensor of an augmented reality (AR) display device. The first sensor data indicates a pose of the AR display device relative to a first reference coordinate system. The server detects a physical object using second sensor data received from a second sensor of the AR display device. The server determines, based on the second sensor data, a pose of the physical object relative to the AR display device. The server then determines the pose of the physical object relative to the first reference coordinate system based on the pose of the physical object relative to the AR display device and the pose of the AR display device relative to the first reference coordinate system.

Remote object detection and local tracking using visual odometry

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Los Angeles, CA, United States of America

Jakob Zillner