Real-time visual SLAM on embedded platforms
ORB-SLAM2 is a visual based SLAM (Simultaneous Localization and Mapping) application that estimates the trajectory of a moving object and at the same time, creates a map of the environment. This allows for good indoor spatial tracking as well as movement tracking. However, the robustness of ORB-SLAM...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
Nanyang Technological University
2020
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/137898 |
| _version_ | 1826126534542360576 |
|---|---|
| author | Chai, Boon Hui |
| author2 | Lam Siew Kei |
| author_facet | Lam Siew Kei Chai, Boon Hui |
| author_sort | Chai, Boon Hui |
| collection | NTU |
| description | ORB-SLAM2 is a visual based SLAM (Simultaneous Localization and Mapping) application that estimates the trajectory of a moving object and at the same time, creates a map of the environment. This allows for good indoor spatial tracking as well as movement tracking. However, the robustness of ORB-SLAM2 is degraded in the presence of moving objects in the scene as the pixels that are selected for referencing between image frames may belong to these dynamic objects. This problem can be mitigated by using semantic segmentation to distinguish between static and dynamic objects in the scene and allow only the pixels of static objects to be used for referencing between image frames. The purpose of this report is to evaluate the performance of combining ORB-SLAM2 and semantic segmentation on an embedded platform. |
| first_indexed | 2024-10-01T06:54:14Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/137898 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:54:14Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1378982020-04-17T08:27:21Z Real-time visual SLAM on embedded platforms Chai, Boon Hui Lam Siew Kei School of Computer Science and Engineering assklam@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision ORB-SLAM2 is a visual based SLAM (Simultaneous Localization and Mapping) application that estimates the trajectory of a moving object and at the same time, creates a map of the environment. This allows for good indoor spatial tracking as well as movement tracking. However, the robustness of ORB-SLAM2 is degraded in the presence of moving objects in the scene as the pixels that are selected for referencing between image frames may belong to these dynamic objects. This problem can be mitigated by using semantic segmentation to distinguish between static and dynamic objects in the scene and allow only the pixels of static objects to be used for referencing between image frames. The purpose of this report is to evaluate the performance of combining ORB-SLAM2 and semantic segmentation on an embedded platform. Bachelor of Engineering (Computer Engineering) 2020-04-17T08:27:21Z 2020-04-17T08:27:21Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/137898 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Chai, Boon Hui Real-time visual SLAM on embedded platforms |
| title | Real-time visual SLAM on embedded platforms |
| title_full | Real-time visual SLAM on embedded platforms |
| title_fullStr | Real-time visual SLAM on embedded platforms |
| title_full_unstemmed | Real-time visual SLAM on embedded platforms |
| title_short | Real-time visual SLAM on embedded platforms |
| title_sort | real time visual slam on embedded platforms |
| topic | Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision |
| url | https://hdl.handle.net/10356/137898 |
| work_keys_str_mv | AT chaiboonhui realtimevisualslamonembeddedplatforms |