Mirror and transparent-objects have been an issue for simultaneous re-localization and mapping (SLAM). Mirrors reflect light rays which cause wrong reconstructions and windows can not directly be measured by the depth camera. This is especially dangerous for robotic applications, since robots may try to go into a mirror or go through a window. The main goal of this work is to solve this issue by detecting mirrors/windows and reconstructing a correct map.
The potential approach is to use an object detection network, such as YOLO, to detect possible mirrors and windows. Then designing a function to correctly reconstruct the reflected region in the map.
This work involves knowledge in deep learning and SLAM.
Python and C++
Deep learning in Object detection.
Computer vision and multiview geometry