These data sets are designed to be used with the Transform Flow Visualisation tool. They are designed for sample usage, algorithm development, and testing/evaluation.
Simply use the transform-flow-visualisation command line tool, and point it to one of the data directories.
Several of these data sets have been designated standard and can be referred to in research using a code:
2013A | 2013 University of Canterbury/VideoStream-2013-07-09-16-04-47
2013B | 2013 University of Canterbury/VideoStream-2013-07-09-17-58-39
When using a particular tracking point data set, append the tracking point index to the data set name, e.g. 2013A0.
Currently, camera intrinsics are not captured, as these are not available automatically. By default, iPhone video frames are captured with a ~55degree field of view. In the future we may try to rectify this by including some type of camera intrinsics configuration along with the data set.
The data sets are deliberately compressed using 80% quality JPEG. The data capture tool captures high quality PNG files. To convert your files, use image magick:
$ cd VideoStream-my-data-set
$ mogrify -format jpg -quality 80% *.png
$ rm *.png
You may wish to keep your PNG data sets, but in order to keep the repository size managable, we require JPEG only. Please use the exact conversion routine outlined above.
- Fork it
- Create your feature branch (
git checkout -b at-the-beach) - Commit your data sets (
git commit -am 'At the beach') - Push to the branch (
git push origin at-the-beach) - Create new Pull Request
This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.
Copyright, 2013, by Samuel G. D. Williams.
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