Intelligent projection point prediction for overhead objects

A method, comprising:

• receiving one or more two-dimensional (2D) training images of one or more unique overhead objects within an environment;
• processing the 2D training images to determine one or more training positions of each overhead object and one or more training positions of projection points of each overhead object;
• based on at least the training positions of the overhead objects, training one or more artificial intelligence (AI) models to predict 2D positions of projection points of the overhead object;
• receiving one or more 2D inference images of the overhead objects captured by one or more cameras within the environment;
• processing the 2D inference images to determine one or more inferred positions of the overhead objects;
• predicting, via the one or more trained AI models and using the inferred positions of the overhead objects as input, 2D inferred positions of the projection points of the overhead objects;
• and
• providing, to one or more client devices, the predicted 2D inferred positions of the projection points of the overhead objects;
• wherein training the one or more AI models comprises normalizing the training positions of the overhead objects and the training positions of the projection points of the overhead objects to a range between 0 and 1, and wherein training the one or more AI models further comprises applying coordinate transformation to the normalized training positions of the overhead objects and the normalized training positions of the projection points of the overhead objects, and wherein applying coordinate transformation comprises defining the normalized training positions of the overhead objects and the normalized training positions of the projection points of the overhead objects as relative to the bottom center of a bounding box for the overhead objects.

A method, comprising:

• receiving one or more two-dimensional (2D) training images of one or more unique overhead objects within an environment;
• processing the 2D training images to determine one or more training positions of each overhead object and one or more training positions of projection points of each overhead object;
• based on at least the training positions of the overhead objects, training one or more artificial intelligence (AI) models to predict 2D positions of projection points of the overhead object;
• receiving one or more 2D inference images of the overhead objects captured by one or more cameras within the environment;
• processing the 2D inference images to determine one or more inferred positions of the overhead objects;
• predicting, via the one or more trained AI models and using the inferred positions of the overhead objects as input, 2D inferred positions of the projection points of the overhead objects;
• and
• providing, to one or more client devices, the predicted 2D inferred positions of the projection points of the overhead objects;
• wherein predicting the 2D inferred positions of the projection points of the overhead objects comprises normalizing the inferred positions of the overhead objects to a range between 0 and 1, and wherein predicting the 2D inferred positions of the projection points of the overhead objects comprises applying coordinate transformation to the normalized actual positions of the overhead objects, and wherein applying coordinate transformation comprises defining the normalized inferred positions of the overhead objects as relative to the bottom center of a bounding box for the overhead objects.