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TUM RGB-D Scribble-based Segmentation Benchmark

Description

The RGB-D dataset contains the following

  • The number of RGB-D images is 154, each with a corresponding scribble and a ground truth image.
  • Every image has a resolution of 640 × 480 pixels.
  • The measurement of the depth images is millimeter.
  • The categorization differentiates between 95 classes.
  • All scenes are indoor.
LabeledImagesThis folder includes all images with the naming convention: [scene]_[number]_[image type].png, where scene is either bedroom, kitchen, livingroom or random and image type is either image, depth, scribbles or gt.
RawDataIn this folder the original data in .xcf format can be found.
UnalignedDepthOne can find here all depth images before they were registered.
rgbd_palette.gplThe ground truth and scribble images are converted to indexed mode. The related color palette is saved in this file.
LabelColorMapping.csvThis file describes which color belongs to which object class.
displayLabeledImages.pyFor visualization this script provides an overview of one image with the associated classes.
CalibrationThis folder contains the scripts, parameters and the images which were used for finding the parameters and for registering the depth images.

Example

./LabeledImages/kitchen_22_image.png./LabeledImages/kitchen_22_gt.png
./LabeledImages/kitchen_22_depth.png./LabeledImages/kitchen_22_scribbles.png

For visualizing the point cloud, this matlab script can be used.

figure( 1, "visible", "off" );
depth = imread('LabeledImages/kitchen_22_depth.png');
depth = double(depth);
img = imread('LabeledImages/kitchen_22_image.png');
surf(depth, img, 'FaceColor', 'texturemap', 'EdgeColor', 'none' )
view(158, 38)
print -dpng pointCloud.png;
ans = "pointCloud.png";

pointCloud.png

Citation

If you use the dataset, please cite as following

@misc{tum-rgbd_scribble_dataset,
 author    = {Caner Hazirbas and Andreas Wiedemann and Robert Maier and Laura Leal-Taixé and Daniel Cremers},
 title     = {TUM RGB-D Scribble-based Segmentation Benchmark},
 howpublished = {\url{https://github.com/tum-vision/rgbd_scribble_benchmark}},
 year = {2018}
}