Vehicle environment modeling with a camera

A device for modeling a road surface, the device comprising:

• a hardware interface to obtain a time-ordered sequence of images representative of a road surface, the time-ordered sequence of images captured by a sensor, one of the sequence of images being a current image;
• and
• processing circuitry to:
• provide a data set to an artificial neural network (ANN), the ANN trained with an unsupervised training technique in which error is determined by a difference in road structure of overlapping segments between two images at two different times from the sequence of images, wherein the inference is performed on the first image, and wherein the overlapping segment is closer to the sensor in the second image, the ANN to produce a three-dimensional structure of a scene, the data set including:
• a portion of the sequence of images, the portion of the sequence of images including the current image;
• motion of the sensor that captured the sequence of images;
• and
• an epipole;
• and
• model the road surface using the three-dimensional structure of the scene.