Mobileye Vision Technologies Ltd.

Jeffrey Moskowitz

Nadav Shaag

Gideon Stein

Itay Blumenthal

Natalie Carlebach

Ofer Springer

David Neuhof

Gal Topel

Yotam Stern

Erez Dagan

Kevin Rosenblum

Shahar Harouche

Roy Maor Lotan

Alon Ziv

David Boublil

Daniel Einy

Chaim Blau

System and techniques for vehicle environment modeling with a camera are described herein. A device for modeling an environment comprises: a hardware sensor interface to obtain a sequence of unrectified images representative of a road environment, the sequence of unrectified images including a first unrectified image, a previous unrectified image, and a previous-previous unrectified image; and processing circuitry to: provide the first unrectified image, the previous unrectified image, and the previous-previous unrectified image to an artificial neural network (ANN) to produce a three-dimensional structure of a scene; determine a selected homography; and apply the selected homography to the three-dimensional structure of the scene to create a model of the road environment.

Vehicle environment modeling with a camera

A navigation system for a host vehicle may include a processor programmed to: receive from a camera onboard the host vehicle at least one captured image representative of an environment of the host vehicle, wherein the camera is positioned at a first location relative to the host vehicle; receive point cloud information from a LIDAR system onboard the host vehicle, wherein the LIDAR system is positioned at a second location relative to the host vehicle; analyze the at least one captured image and the received point cloud information to detect one or more objects in the shared field of view region; determine whether a vantage point difference between the first location of the camera and the second location of the LIDAR system accounts for the one or more detected objects being represented in only one of the at least one captured image or the received point cloud information.

LIDAR-camera fusion where LIDAR and camera validly see different things

System and techniques for vehicle environment modeling with a camera are described herein. A time-ordered sequence of images representative of a road surface may be obtained. An image from this sequence is a current image. A data set may then be provided to an artificial neural network (ANN) to produce a three-dimensional structure of a scene. Here, the data set includes a portion of the sequence of images that includes the current image, motion of the sensor from which the images were obtained, and an epipole. The road surface is then modeled using the three-dimensional structure of the scene.

Various systems and methods for modeling a scene. A device for modeling a scene includes a hardware interface to obtain a time-ordered sequence of images representative of a scene, the time-ordered sequence including a plurality of images, one of the sequence of images being a current image, the scene captured by a monocular imaging system; and processing circuitry to: provide a data set to an artificial neural network (ANN) to produce a three-dimensional structure of the scene, the data set including: a portion of the sequence of images, the portion of the sequence of images including the current image; and motion of a sensor that captured the sequence of images; and model the scene using the three-dimensional structure of the scene, wherein the three-dimensional structure is determined for both moving and fixed objects in the scene.

Vehicle environment modeling with cameras

A navigation system for a host vehicle may include a processor programmed to: receive from a center camera onboard the host vehicle a captured center image including a representation of at least a portion of an environment of the host vehicle, receive from a left surround camera onboard the host vehicle a captured left surround image including a representation of at least a portion of the environment of the host vehicle, and receive from a right surround camera onboard the host vehicle a captured right surround image including a representation of at least a portion of the environment of the host vehicle; provide the center image, the left surround image, and the right surround image to an analysis module configured to generate an output relative to the at least one captured center image; and cause a navigational action by the host vehicle based on the generated output.

Pseudo lidar

Growing community of inventors

Jerusalem, Israel

Jeffrey Moskowitz