Google Inc.

Google Technology Holdings LLC

Patrick Mihelich

Joel Hesch

Esha D Nerurkar

Ryan Michael Hickman

Johnny Chung Lee

James Fung

Ivan Dryanovski

Renzo De Nardi

Esha Nerurkar

An electronic device includes one or more imaging cameras. After a reset of the device or other specified event, the electronic device identifies an estimate of the device's pose based on location data such as Global Positioning System (GPS) data, cellular tower triangulation data, wireless network address location data, and the like. The one or more imaging cameras may be used to capture imagery of the local environment of the electronic device, and this imagery is used to refine the estimated pose to identify a refined pose of the electronic device. The refined pose may be used to identify additional imagery information, such as environmental features, that can be used to enhance the location based functionality of the electronic device.

Electronic device localization based on imagery

An electronic device includes at least one sensor, a display, and a processor. The processor is configured to determine a dimension of a physical object along an axis based on a change in position of the electronic device when the electronic device is moved from a first end of the physical object along the axis to a second end of the physical object along the axis. A method includes capturing and displaying imagery of a physical object at an electronic device, and receiving user input identifying at least two points of the physical object in the displayed imagery. The method further includes determining, at the electronic device, at least one dimensional aspect of the physical object based on the at least two points of the physical object using a three-dimensional mapping of the physical object.

Measuring dimension of object through visual odometry

Methods and systems for calibrating sensors on a computing device are described herein. In an example implementation, a computing device may perform a method to calibrate one or more sensors, which may include receiving an indication that a sensor has been calibrated. The computing device may further receive independent observations of a motion of a device from the calibrated sensor and a potentially non-calibrated sensor. The device may determine as independent estimation of motion based on the movement of the device corresponding to the outputs of the respective sensors. Based on whether or not the estimation of motion as provided by the potentially non-calibrated sensor is within a threshold variance of the estimation of motion as provided by the calibrated sensor, the computing device may provide instructions to adjust parameters of the non-calibrated sensor.

Methods and systems for calibrating sensors of a computing device

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Sunnyvale, CA, United States of America

Patrick Mihelich