An example driver assistance system includes an object detection (OD) network, a semantic segmentation network, a processor, and a memory. In an example method, an image is received and stored in the memory. An object detection (OD) polygon is generated for each object detected in the image, and each OD polygon encompasses at least a portion of the corresponding object detected in the image. A region of interest (ROI) is associated with each OD polygon. Such method may further comprise generating a mask for each ROI, each mask configured as a bitmap approximating a size of the corresponding ROI; generating at least one boundary polygon for each mask based on the corresponding mask, each boundary polygon having multiple vertices and enclosing the corresponding mask; and reducing a number of vertices of the boundary polygons based on a comparison between points of the boundary polygons and respective points on the bitmaps.
Semantic occupancy grid management in ADAS/autonomous driving
2024-02-06
Patent
Electronic Resource
English
Semantic Occupancy Grid Management in ADAS/Autonomous Driving
European Patent Office | 2023
|Springer Verlag | 2021
|EXTENSIVIEW AND ADAPTIVE LKA FOR ADAS AND AUTONOMOUS DRIVING
European Patent Office | 2021
|EXTENSIVIEW AND ADAPTIVE LKA FOR ADAS AND AUTONOMOUS DRIVING
European Patent Office | 2020
|Semantic 3D Grid Maps for Autonomous Driving
IEEE | 2022
|