Digital image correlation (DIC) and binary markers, such as ArUco markers, are established vision-based tracking methods for positional estimation, and, in case of DIC, strain and deformation information. In this bachelor thesis, both methods are to be compared with respect to their positional accuracy and tracking reliability over time, especially considering factors such as illumination, occlusion and motion of the markers.
The methods can be compared both in a simulation as well as in the real world. For the latter, a linear guide is provided, which provides controlled motion for the DIC speckle patterns and/or ArUco markers with high (sub millimetre-level) precision.
Your task will be to implement and assess one or more tracking systems based on DIC and ArUco markers, and analyze their performance in different experimental setups. The findings could be highly valuable for applications that demand accurate displacement measurements, such as structural health monitoring.
If you are interested in the topic, please contact me via the contact form or simply scan the QR code below.
Good practical experience with Python is required. Prior experience with Blender is also helpful, but not required.
Contact person: Tomas Verardo
