Calibration Best Practices
Accurate calibration is of key importance for performance most machine and computer vision tasks. This article goes over the best practices that we have found through extensive experimentation over the years.
- Choose the right size calibration target. Large enough to properly constrain parameters. Preferably it should cover approx. half of the total area when seen fronto-parallel in the camera images.
- Perform calibration at the approximate working distance (WD) of your final application. The camera should be focused at this distance and focus should be unchanged after calibration.
- The target should have a high feature count. Using fine patterns is preferable. However, at some point detection robustness suffers. Our recommendation is to use fine pattern counts for cameras above 3MPx and if the lighting is controlled and good.
- Collect images from different areas and tilts. Move the target to fully cover the image area and aim for even coverage. Lens distortion can be properly determined from fronto-parallel images only, but focal length estimation is dependent on observing foreshortening. Include both frontoparallel images, and images taken with the board tilted up to +/- 45 degrees in both horizontal an vertical direction. Tilting more is usually not a good idea as feature localization accuracy suffers.
- Use good lighting. This is often overlooked, but hugely important. The calibration target should preferably be diffusely lit by means of controlled photography lighting. Strong point sources give rise to uneven illumination, possibly making detection fail, and not utilizing the camera's dynamic range very well. Shadows can do the same.
- Have enough observations. Usually, calibration should be performed on at least 6 observations (images) of a calibration target. If a higher order camera or distortion model is used, more observations are beneficial.
- Consider using uniquely coded targets such as CharuCo boards. These allow you to gather observations from the very edges of the camera sensor and lens, and hence constrain the distortion parameters very well. Also, they allow you to collect data even when single feature points do not fulfill the other requirements.
- Calibration is only as accurate as the calibration target used. Use laser printed targets only to validate and test.
- Proper mounting of calibration target and camera. In order to minimize distortion and bow in larger targets, mount them either vertically, or laying flat on a rigid support. Consider moving the camera in these cases instead. Use a quality tripod, and avoid touching the camera during acquisitions.
- Remove bad observations. Carefully inspect reprojection errors. Both per-view and per-feature. If any of these appear as outliers, exclude them and recalibrate.
Following these practices should ensure the most accurate and precise calibration possible.
Have any questions, comments or additional insights? Post them below.