University of Twente Student Theses
Lightweight image-based key point tracking for real-time bridge monitoring with smartphones
Hu, X.L. (2021) Lightweight image-based key point tracking for real-time bridge monitoring with smartphones.
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| Abstract: | Key point detection has become more relevant in many industries. From maintenance to development of materials. The usage of this technology is not equally distributed. Some sectors have been more integrated with this technique than others. The bridge maintenance sector still uses IMU(Inertial movement unit) sensors for their inspection of critical points on bridges. This is quite outdated since for large bridges many IMU sensors are needed. We made an application which can estimate the movement of critical points using a video taken from a smartphone. This will aid in more efficient performance and lower the cost of bridge maintenance. Since less to no IMU sensors will be needed to perform the check up. As IMU sensors can take a couple of hours to be placed and removed from the bridge. Their data needs to be progressed and calibrated which could take a couple. In the future, this application could replace the IMU sensors completely and result in efficient and less time consuming bridge maintenance. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/87067 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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