Systems and methods for end-to-end map building from a video sequence using neural camera models
AssigneeToyota Research Institute, Inc.
InventorsVitor Guizilini, Igor Vasiljevic, Rares A. Ambrus, Sudeep Pillai, Adrien Gaidon
Life of this patent
Estimating the term…
Abstract
Systems and methods for map construction using a video sequence captured on a camera of a vehicle in an environment, comprising: receiving a video sequence from the camera, the video sequence including a plurality of image frames capturing a scene of the environment of the vehicle; using a neural camera model to predict a depth map and a ray surface for the plurality of image frames in the received video sequence; and constructing a map of the scene of the environment based on image data captured in the plurality of frames and depth information in the predicted depth maps.
Claims24
A method of metric map construction using a video sequence captured on a camera of a vehicle in an environment, comprising:
- receiving a video sequence from the camera, the video sequence comprising a plurality of image frames capturing a scene of the environment of the vehicle;
- using a neural camera model to predict a depth map and a ray surface for the plurality of image frames in the received video sequence;
- and
- constructing a metric map of the scene of the environment based on image data captured in the plurality of frames and depth information in the predicted depth map.
A system for metric map construction using a video sequence captured on a camera of a vehicle in an environment, the system comprising:
- a non-transitory memory configured to store instructions;
- a processor configured to execute the instructions to perform the operations of:
- receiving a video sequence from the camera, the video sequence including a plurality of image frames capturing a scene of the environment of the vehicle;
- using a neural camera model to predict a depth map and a ray surface for the plurality of image frames in the received video sequence;
- and
- constructing a metric map of the scene of the environment based on image data captured in the plurality of image frames and depth information in the predicted depth map.
Dependencies are inferred from the claim text.