Optical flow determination system

A method comprising:

• examining camera-based images of interior surfaces of equipment that are moving relative to a camera that generated the camera-based images using a generator sub-network of a generative adversarial network (GAN) system;
• generating one or more distribution-based images using the generator sub-network based on the camera-based images that were examined by the generator sub-network;
• examining the one or more distribution-based images using a discriminator sub-network of the GAN system to determine whether the one or more distribution-based images accurately represent the interior surfaces of the equipment;
• responsive to determining that the one or more distribution-based images accurately represent the interior surfaces of the equipment using the discriminator sub-network, determining a predicted optical flow of the interior surfaces of the equipment abased on the one or more distribution-based images;
• and
• generating a three-dimensional (3D) point cloud using the predicted optical flow of the interior surfaces, the 3D point cloud depicting an interior of the equipment.

A system comprising:

• a generator sub-network configured to examine camera-based images of a moving object, the generator sub-network also configured to generate one or more distribution-based images based on distributions of pixel characteristics in the camera-based images;
• a discriminator sub-network configured to examine the one or more distribution-based images to determine one or more errors between the one or more distribution-based images and the camera-based images of the moving object, the one or more errors indicative of whether the one or more distribution-based images accurately represent the moving object,
• wherein a predicted optical flow of the moving object is represented by relative movement of the object as shown in the one or more distribution-based images;
• and
• one or more processors configured to generate a three-dimensional (3D) point cloud representative of the moving object, the 3D point cloud generated using the predicted optical flow of the moving object.