Right track - A google map companion using junction recognition
The challenge of navigating complex road systems, especially in urban environments, necessitates innovative solutions to enhance driver safety and confidence. This project explores the development of a computer vision system aimed at detecting road junctions in real-time, providing drivers with time...
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| Format: | Final Year Project / Dissertation / Thesis |
| Published: |
2023
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| Online Access: | http://eprints.utar.edu.my/6044/ http://eprints.utar.edu.my/6044/1/fyp_CS_2023_TYM.pdf |
| _version_ | 1848886573486047232 |
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| author | Tan, Yong Ming |
| author_facet | Tan, Yong Ming |
| author_sort | Tan, Yong Ming |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | The challenge of navigating complex road systems, especially in urban environments, necessitates innovative solutions to enhance driver safety and confidence. This project explores the development of a computer vision system aimed at detecting road junctions in real-time, providing drivers with timely and accurate guidance. The system comprises two key components: junction detection and image similarity comparison. Traditional object detection metrics, such as Intersection over Union (IOU), are ill-suited for the intangible nature of junctions. As a solution, we propose the use of accuracy as an alternative evaluation metric to assess the model's ability to classify frames as 'junction present' or 'no junction.' Ground truth labeling of test images as '1' or '0' is performed, facilitating accuracy evaluation. This project's computer vision model demonstrated significant progress in junction detection accuracy, enhancing driver safety and navigation. Challenges encountered provide valuable insights for future refinement, particularly in optimizing cloud-based processing efficiency. The findings contribute to the advancement of intelligent navigation systems in complex urban environments. |
| first_indexed | 2025-11-15T19:40:39Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-6044 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:40:39Z |
| publishDate | 2023 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-60442024-01-02T14:55:36Z Right track - A google map companion using junction recognition Tan, Yong Ming T Technology (General) TD Environmental technology. Sanitary engineering TH Building construction The challenge of navigating complex road systems, especially in urban environments, necessitates innovative solutions to enhance driver safety and confidence. This project explores the development of a computer vision system aimed at detecting road junctions in real-time, providing drivers with timely and accurate guidance. The system comprises two key components: junction detection and image similarity comparison. Traditional object detection metrics, such as Intersection over Union (IOU), are ill-suited for the intangible nature of junctions. As a solution, we propose the use of accuracy as an alternative evaluation metric to assess the model's ability to classify frames as 'junction present' or 'no junction.' Ground truth labeling of test images as '1' or '0' is performed, facilitating accuracy evaluation. This project's computer vision model demonstrated significant progress in junction detection accuracy, enhancing driver safety and navigation. Challenges encountered provide valuable insights for future refinement, particularly in optimizing cloud-based processing efficiency. The findings contribute to the advancement of intelligent navigation systems in complex urban environments. 2023-06 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/6044/1/fyp_CS_2023_TYM.pdf Tan, Yong Ming (2023) Right track - A google map companion using junction recognition. Final Year Project, UTAR. http://eprints.utar.edu.my/6044/ |
| spellingShingle | T Technology (General) TD Environmental technology. Sanitary engineering TH Building construction Tan, Yong Ming Right track - A google map companion using junction recognition |
| title | Right track - A google map companion using junction recognition |
| title_full | Right track - A google map companion using junction recognition |
| title_fullStr | Right track - A google map companion using junction recognition |
| title_full_unstemmed | Right track - A google map companion using junction recognition |
| title_short | Right track - A google map companion using junction recognition |
| title_sort | right track - a google map companion using junction recognition |
| topic | T Technology (General) TD Environmental technology. Sanitary engineering TH Building construction |
| url | http://eprints.utar.edu.my/6044/ http://eprints.utar.edu.my/6044/1/fyp_CS_2023_TYM.pdf |