Small Assignment 2, CIE4614, 3D Surveying

Small Assignment 2, CIE4614, 3D Surveying
• Maximal 2 students per report. Please put your names and student numbers on the assignment.
• Upload a report of your answers in pdf on Brightspace until Friday, March 4, 23.59 CET.
• Give pseudocode for steps you programmed yourself and/or list built-in commands.
• Clearly refer to information from documents and websites.
Goal of this assignment is to calibrate your own camera, like your own digital single lense reflect
(SLR) camera, or the one in your mobile phone. Old cameras probably give more distortion and
are therefore advised. Calibration will be done using a chessboard pattern to estimate its interior
parameters. The interior orientation is preferably estimated before you use your camera on
location. This assignment involves the fundamental principle of photogrammetry: the collinear
equations.
Use predefined functions in OpenCV (Python or C++) or use your own program.
1. What are the interior parameters of a camera? Name and explain the concept op each
parameter.
2. What are the camera’s distortion parameters? Name and explain these parameters.
3. Why chessboards are widely used for camera calibration? What do they provide?
4. Describe your camera including its lens. Take two images of a chessboard. Explain why
the chessboard should cover the full extent of your images.
5. Apply the corner detection algorithm on both images and display the found corners.
6. Create an array or vector to store the 3D coordinates in a world coordinate system. Explain how you created it. What are the Z values/coordinates of each points? Why?
7. Apply the camera calibration algorithm and explain the outputs. (Hint: it gives more than
just interior and distortion parameters)
8. Use your distortion parameters to rectify your image. Display the results.
9. Use your output parameters to obtain for one 3D point its corresponding image position
by using the collinearity equations or an equivalent matrix multiplication in a suitable
projection. Does your 3D point match a corner in the image?