Neural network object pose determination

A system, comprising:

• a camera positioned to obtain an image of an object;
• and
• a computer including a processor and a memory, the memory storing instructions executable by the processor to:
• input the image to a neural network that outputs a three-dimensional (3D) bounding box for the object relative to a pixel coordinate system and object parameters;
• then determine a center of a bottom face of the 3D bounding box in pixel coordinates, wherein the bottom face of the 3D bounding box is located in a ground plane in the image;
• based on calibration parameters for the camera that transform pixel coordinates into real-world coordinates, determine a) a distance from the center of the bottom face of the 3D bounding box to the camera relative to a real-world coordinate system and b) an angle between a line extending from the camera to the center of the bottom face of the 3D bounding box and an optical axis of the camera, wherein the calibration parameters include a camera height relative to the ground plane, a camera focal distance, and a camera tilt relative to the ground plane;
• and
• determine a six degree-of-freedom (6DoF) pose for the object based on the object parameters, the distance, and the angle.