The goal of this assignment is to perform single-view 3D measurements, fundamental matrix estimation, triangulation, and camera calibration.
Be sure to include the following in your report:
- Single-view geometry: See items 1-4 in Part 3 above.
- Fundamental matrix estimation, calibration, triangulation:
- For the lab and library image pairs, display your result (points and epipolar lines) and report your residual for both unnormalized and normalized fundamental matrix estimation.
- For the lab image pair, show your estimated 3x4 camera projection matrices. Report the residual between the projected and observed 2D points.
- For the lab and library image pairs, visualize 3D camera centers and triangulated 3D points.
- For the house and gaudi image pairs, display your result and report your number of inliers and average inlier residual for normalized estimation without ground truth matches.
You must upload the following files on Canvas:
- Your code in two separate files for part 1 and part 2. The filenames should be lastname_firstname_a4_p1.ipynb and lastname_firstname_a4_p2.py. For part 1, you should also output an exported PDF of the notebook as lastname_firstname_a4_p1.pdf (do the same for part 2 if you decide to submit your code as a Python notebook).
- A report in a single PDF file with all your results and discussion for both parts following this template. The filename should be lastname_firstname_a4.pdf.
- All your output images and visualizations in a single zip file. The filename should be lastname_firstname_a4.zip. Note that this zip file is for backup documentation only, in case we cannot see the images in your PDF report clearly enough. You will not receive
credit for any output images that are part of the zip file but are not shown (in some form) in the report PDF.
Please refer to course policies on late submission, academic integrity, etc.