This repository hosts MATLAB script for generating occupancy grid map from a monocular camera frame.
The monocular camera frame (first person view) is passed to a deep neural network trained to estimate free space around a vehicle using semantic segmentation. Free space estimation identifies areas in the environment where the ego vehicle can drive without hitting any obstacles such as pedestrians, curbs, or other vehicles. A vehicle can use a variety of sensors to estimate free space such as RADAR, LiDAR, or cameras. This project focuses on estimating free space from a monocular camera using semantic segmentation and creating an occupancy grid map using the same. This occupancy grid map can be used to create a vehicle costmap, which can be then used for path planning and navigation.
Result | Image |
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Test Frame | ![]() |
First Person View (FPV) | ![]() |
Free Space Prediction [FPV] | ![]() |
Free Space Confidence Scores [FPV] | ![]() |
Bird's Eye View (BEV) | ![]() |
Free Space Confidence Scores [BEV] | ![]() |
Occupancy Grid Map | ![]() |