SPS-Stereo is a dense stereo method employing a slanted plane model. It jointly estimates a superpixel segmentation, boundry labels (such as occlusion boundaries), and a dense depth estimate from a pair of stereo images.
Citation
@inproceedings{Yamaguchi14,
author = {Koichiro Yamaguchi and David McAllester and Raquel Urtasun},
title = {Efficient Joint Segmentation, Occlusion Labeling, Stereo and Flow Estimation},
booktitle = {ECCV},
year = {2014}
}
First, download KITTI stereo/flow dataset from KITTI Vision Benchmark Suite homepage and extract it.
Run SPS-Stereo
> ./spsstereo data_stereo_flow/training/image_0/000000_10.png data_stereo_flow/training/image_1/000000_10.png
Outputs
-
000000_10_disp.png
Disparity image (PNG 16bit grayscale format)
(Disparity value) = (Pixel value)/256.0 -
000000_10L_seg.png
Segmentation image (PNG 16bit grayscale format)
(Segment ID) = (Pixel value) -
000000_10L_plane.png
Estimated disparity planes
the number of lines = the number of segments
Each line includes parameters of disparity plane of a segment:(A_i, B_i, C_i)
-
000000_10L_label.txt
Boundary labeling result
the number of lines = the number of boundaries
Each line includes three entries:SegmentID1 SegmentID2 boundary_label
boundary_label
: 0 (Occlusion, SegmentID1 is front), 1 (Occlusion, SegmentID2 is front), 2 (Hinge), 3 (Coplanar) -
000000_10L_boundary.png
Visualization of segmentation result
Boundary color means a type of relationship between neighboring segments: Red/Blue-Occluion (Red side is front), Green-Hinge, Gray- Coplaner
SPS-Stereo is licensed under the GNU General Public License Version 3 (GPLv3), see http://www.gnu.org/licenses/gpl.html.