Reflection Aware Visual Simultaneous Localization and Mapping (RA-vSLAM)

Lead Research Organisation: Cardiff University


Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.




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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/T517951/1 30/09/2020 29/09/2025
2435656 Studentship EP/T517951/1 30/09/2020 29/09/2024
Description The first aim of the work funded was to understand the influence of visual reflections in current vSLAM. To achieve this, a dataset was collected and used to evaluate existing vSLAM methods in environments containing mirrors. The results of the analysis has passed peer review, and is due for publication.
Exploitation Route The outcomes from this work will continue to motivate development of robust systems and their constituent components (such as feature extraction) in challenging environments containing mirrors. This will have impacts in academic areas (such as mirror detection and planar symmetry detection tasks in computer vision), as well as for applications such as autonomous navigation, AR/VR and 3D reconstruction.
Sectors Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Electronics

Title MirrEnv 
Description The MirrEnv dataset comprises 49 RGB-D image sequences taken in environments containing planar mirror reflections. A robotic arm was used to collect group truth localisation positions for each sequence. These sequences can be grouped into 7 different trajectory paths, each of these groups containing sequences with different size mirrors present or covered over. 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? No  
Impact This dataset was used to analyse existing visual SLAM methods in mirrored environments and motivate further development of robust visual SLAM systems. this dataset might also be used in the future for developing new methods to tackle these challenging scenarios.