NVIDIA Corporation
PROJECTING IMAGES CAPTURED USING FISHEYE LENSES FOR FEATURE DETECTION IN AUTONOMOUS MACHINE APPLICATIONS

Abstract:

In various examples, live perception from wide-view sensors may be leveraged to detect features in an environment of a vehicle. Sensor data generated by the sensors may be adjusted to represent a virtual field of view different from an actual field of view of the sensor, and the sensor data--with or without virtual adjustment--may be applied to a stereographic projection algorithm to generate a projected image. The projected image may then be applied to a machine learning model--such as a deep neural network (DNN)--to detect and/or classify features or objects represented therein. In some examples, the machine learning model may be pre-trained on training sensor data generated by a sensor having a field of view less than the wide-view sensor such that the virtual adjustment and/or projection algorithm may update the sensor data to be suitable for accurate processing by the pre-trained machine learning model.