In this project, we study the role of high-level geometric topological cues such as 3D primitive representation of indoor corridors to improve the performance of simultaneous localization and modelling (SLAM) using a low-cost monocular camera. We aim to develop computer vision systems for automatically reconstructing 3D manhattan models to represent an indoor corridor from monocular imagery, and integrate it within SLAM framework.
Grant Agency: ORF Research Excellence – Intelligent Systems for Sustainable Urban Mobility (ISSUM)