Towards Visual-Inertial SLAM for Dynamic Environments Using Instance Segmentation and Dense Optical Flow
Dynamic environments pose an open problem for the performance of visual SLAM systems in real-life scenarios. Such environments involve dynamic objects that can cause pose estimation errors. Recently, Deep Learning semantic segmentation networks have been employed to identify potentially moving objec...
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Format: | Others |
Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2021
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Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-305443 |