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.

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