Khalid Mohamed Naguib Elmadawi

3D semantic segmentation using camera-lidar sensor fusion for autonomous driving / التقسيم الجزئى ثلاثى الأبعادب استخدام دمج مستشعر الكامير او الليدار للقيادة الذاتية Khalid Mohamed Naguib Elmadawi ; Supervised Hanan Ahmed Kamal , Omar Ahmed Nasr - Cairo : Khalid Mohamed Naguib Elmadawi , 2021 - 79 P. : charts , facsimiles ; 30cm

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electronics and Communication

This research improves the environment sensing in control systems through multi-sensor fusion. We are fusing Camera raw image data with LiDAR Point cloud resulting from having a colored point cloud, represented in a spherical grid map representation. We used the fused data in early and mid-level fusion algorithms. We evaluate our algorithms on the KITTI dataset, which provides semantic segmentation for different classes such as Cars, Pedestrians, and cyclists. We evaluated our work on two states of art architectures, namely Squeeze Seg and Point Seg, resulting in improving the mIOU score to 10% in both cases relative to the LiDAR only baseline



Early Fusion Environment Perception Sensor Fusion