Abstract: Techniques and systems are provided for generating depth information for an image. For instance, a process can include obtaining one or more images of an environment. The process can further include generating a set of features for the one or more images. The process can also include combining the set of features with one or more distance maps to generate combined feature distance information, wherein the one or more distance maps indicate distances based on relative height above a ground level. The process can further include generating depth information of the environment based on the combined feature distance information, and outputting the depth information of the environment.

Abstract: The invention relates to a method for operating a driver assistance system (2) of a motor vehicle (1), including a) Capturing an environment (4) of the motor vehicle (1) by a capturing device (3) of the driver assistance system (2); b) Detecting an accessible freespace (6) in the captured environment (4) by a computing device (5) of the driver assistance system (2); c) Detecting and Classifying at least one object (7a-7e) in the captured environment (4) that is located at a border (8) of the freespace (6) by a neural network (9) of the driver assistance system (2); d) Assigning a part (10a-10e) of the border (8) of the freespace (6) to the detected and classified object (7a-7e); and e) Categorizing a part (11a-11e) of the freespace (6) adjacent to the part (10a-10e) of the border (8) that is assigned to the detected and classified object (7a-7e) in dependence upon the class of that classified object (7a-7e), so as to enable improved safety in driving.

Abstract: The invention relates to a method for operating a driver assistance system (2) of a motor vehicle (1), including a) Capturing an environment (4) of the motor vehicle (1) by a capturing device (3) of the driver assistance system (2); b) Detecting an accessible freespace (6) in the captured environment (4) by a computing device (5) of the driver assistance system (2); c) Detecting and Classifying at least one object (7a-7e) in the captured environment (4) that is located at a border (8) of the freespace (6) by a neural network (9) of the driver assistance system (2); d) Assigning a part (10a-10e) of the border (8) of the freespace (6) to the detected and classified object (7a-7e); and e) Categorizing a part (11a-11e) of the freespace (6) adjacent to the part (10a-10e) of the border (8) that is assigned to the detected and classified object (7a-7e) in dependence upon the class of that classified object (7a-7e), so as to enable improved safety in driving.