Abstract: A method and system for training a machine learning model for point of gaze prediction simultaneously analyzes the image of the scene and the image of the driver's face using the machine learning model to generate a point of gaze of a driver in traffic environments. The machine learning model comprises a camera calibration module that can compute an embedding vector that represents the spatial configuration between the driver and the camera system. The camera calibration module improves the overall model's performance, which is jointly trained end to end.