Place recognition for indoor navigation
Visual localization related technology has been deeply researched in the recent years, with increasing development in the field of robotics and autonomous vehicle. The project aims to develop an embedded place recognition system to aid navigation in an indoor environment. The FastABLE algorithm wa...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2020
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| Online Access: | https://hdl.handle.net/10356/137997 |
| _version_ | 1826109927714717696 |
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| author | Wee, Jun Hao |
| author2 | Lam Siew Kei |
| author_facet | Lam Siew Kei Wee, Jun Hao |
| author_sort | Wee, Jun Hao |
| collection | NTU |
| description | Visual localization related technology has been deeply researched in the recent years, with increasing development in the field of robotics and autonomous vehicle.
The project aims to develop an embedded place recognition system to aid navigation in an indoor environment. The FastABLE algorithm was adopted to provide the vision-based methods suitable for mobile devices.
The FastABLE algorithm utilizes a set of test and training image sequences to run low level binary sequence extraction using the global binary descriptor and fast matching technique.
This meets the requirement of low memory and computational cost to develop a visual navigation system that runs on embedded platforms.
The report entails the testing and optimization process of the FastABLE algorithm and the FastABLE android application. The experimental results from the optimized FastABLE android application were subsequently evaluated, achieving average processing time of 1minute 40seconds and average accuracy rate of 48%. |
| first_indexed | 2024-10-01T02:26:26Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/137997 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:26:26Z |
| publishDate | 2020 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1379972020-04-21T08:22:42Z Place recognition for indoor navigation Wee, Jun Hao Lam Siew Kei School of Computer Science and Engineering assklam@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Computer graphics Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Visual localization related technology has been deeply researched in the recent years, with increasing development in the field of robotics and autonomous vehicle. The project aims to develop an embedded place recognition system to aid navigation in an indoor environment. The FastABLE algorithm was adopted to provide the vision-based methods suitable for mobile devices. The FastABLE algorithm utilizes a set of test and training image sequences to run low level binary sequence extraction using the global binary descriptor and fast matching technique. This meets the requirement of low memory and computational cost to develop a visual navigation system that runs on embedded platforms. The report entails the testing and optimization process of the FastABLE algorithm and the FastABLE android application. The experimental results from the optimized FastABLE android application were subsequently evaluated, achieving average processing time of 1minute 40seconds and average accuracy rate of 48%. Bachelor of Engineering (Computer Engineering) 2020-04-21T08:22:42Z 2020-04-21T08:22:42Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/137997 en SCSE19-0119 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Computer graphics Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Wee, Jun Hao Place recognition for indoor navigation |
| title | Place recognition for indoor navigation |
| title_full | Place recognition for indoor navigation |
| title_fullStr | Place recognition for indoor navigation |
| title_full_unstemmed | Place recognition for indoor navigation |
| title_short | Place recognition for indoor navigation |
| title_sort | place recognition for indoor navigation |
| topic | Engineering::Computer science and engineering::Computing methodologies::Computer graphics Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision |
| url | https://hdl.handle.net/10356/137997 |
| work_keys_str_mv | AT weejunhao placerecognitionforindoornavigation |