I recently started to experiment with computer vision. There are still very few code examples out on the Internet, but I found Martin Peris's blog where he published few examples on computer vision. Notably his post on 3D reconstruction with OpenCV and Point Cloud Library (PCL) is a very good one and I used the code to do 3D reconstruction of Karlsruhe dataset by Andreas Geiger and his colleagues. The image pair I used was the first one from the sequence named "2010_03_09_drive_0019".
Here are the source images from 2010_03_09_drive_0019 sequence:
Left image:
Right image:
Disparity image obtained with LIBELAS library:
The disparity image actually is a LEFT disparity image, since the LIBELAS library generates a pair of disparity images - in this case probably computed as left-to-right disparity. I did not use the R disparity image that was generated.
Please excuse the orientation of the point cloud since I am a real beginner with PCL and its viewer is hard to control for me (behaves a bit weird :)).
The resulting point cloud images from various angles are below:
All the images can also be found in a single image gallery.
Please note that the original Karslruhe datased is licensed under Creative Commons by-nc-sa 3.0 license so all my derivative images have the same licensing terms.
hello sir,
OdpovědětVymazatI have been also trying to create 3d point clouds using my own images but could not get good result. thus i consider to use the image as used by you. Please kindly could you tell me what parameter you used for the Q matrix in these images??