Vehicle sensor point cloud probability density function estimation based on vision sensor data

Abstract

Techniques for using machine learning to produce vehicle location sensor data from vision sensor data are disclosed. By using a limited amount of vehicle location sensor data together with vision sensor data, a deep learning network can be trained to produce estimated vehicle location sensor point cloud distributions from, e.g., vision sensor data alone. Using a deep learning network trained in this way, vehicles with limited or no sensor functionality can be equipped with a camera to produce estimated vehicle location sensor point cloud distributions. These estimated vehicle location sensor point cloud distributions can then be compared with general sensor point cloud distributions to improve detection of vehicles, environmental objects, and ghost objects, and subsequently used to improve vehicle safety through vehicle controls or driver notifications and/or to produce enhanced sensor data.