Honda Motor Co., Ltd.

Daqri, LLC

Aniket Murarka

Ananth Ranganathan

Jacob V Menashe

Wenyi Zhao

Kikuo Fujimura

Nils Einecke

Christopher Broaddus

Yan Lu

Lawrence Arnold Gunn

Brendan Drew

Chen-Chi Chu

Yuncong Chen

Varun Nasery

Systems and techniques for sign based localization are provided herein. Sign based localization may be achieved by capturing an image of an operating environment around a vehicle, extracting one or more text candidates from the image, detecting one or more line segments within the image, defining one or more quadrilateral candidates based on one or more of the text candidates, one or more of the line segments, and one or more intersections of respective line segments, determining one or more sign candidates for the image based on one or more of the quadrilateral candidates and one or more of the text candidates, matching one or more of the sign candidates against one or more reference images, and determining a location of the vehicle based on a match between one or more of the sign candidates and one or more of the reference images.

Sign based localization

Techniques of augmented reality device calibration are disclosed. In some example embodiments, a system calibrates a visual inertial navigation (VIN) camera of a head mounted display (HMD) device with at least one eye camera of the HMD device to generate multi-camera calibration parameters, calibrating the at eye camera(s) with a display module of the HMD to generate display calibration parameters, calibrating the IMU with the VIN camera to generate VIN calibration parameters, and calibrating the IMU to the display module using the multi-camera calibration parameters, the display calibration parameters, and the VIN calibration parameters.

Efficient augmented reality display calibration

A computer-implemented method and a system for vehicle localization. The method includes identifying expected lane lines based on a lane level map and a position of a vehicle and identifying observed lane lines based on images captured by an imaging device of the vehicle and the position of the vehicle. The method includes matching the expected lane lines to the observed lane lines and determining a likelihood score based on the matching. The method includes determining a best vehicle pose based on the likelihood score.

System and method for lane vehicle localization with lane marking detection and likelihood scoring

A system and method for mapping, localization and pose correction including, determining a current position of a vehicle along a travel route and a set of currently observable landmarks along the travel route relative to the current position, the set of currently observable landmarks extracted from one or more stereo images obtained from an imaging device, and querying a survey landmark database to identify a subset of surveyed landmarks relative to the current position of the vehicle. The method including determining one or more two-dimensional transform estimates between the set of currently observable landmarks and the subset of surveyed landmarks and identifying a best transform estimate from the one or more two-dimensional transform estimates that minimizes distances between the set of currently observable landmarks and the subset of surveyed landmarks. The method including correcting a pose of the vehicle based on the best transform estimate.

System and method for image based mapping, localization, and pose correction of a vehicle with landmark transform estimation

System and method for mapping, localization and pose correction of a vehicle based on images

A computer-implemented method for generating a depth map including, generating an initial depth map for a first image, the first image being one of a pair of stereo images received from an imaging device, the pair of stereo images including the first image and a second image and generating an estimated depth map based on the initial depth map by hypothesizing depth values for missing regions in the initial depth map. The method including warping the second image based on the estimated depth map, generating a warped depth map based on the first image and the warped second image, and generating a new depth map for the first image relative to the second image based on the warped depth map and the estimated depth map.

System and method for generating a depth map through iterative interpolation and warping

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San Jose, CA, United States of America

Aniket Murarka