This repository contains color images of natural scenes with non-overdetailed objects together with pixel-by-pixel color-based segmentation annotations. The dataset consists of 3 distinct parts (sub-datasets), any of which fully acquired with the use of a single camera sensor:
- Selected-SFU
- IITP-close
- IITP-diffuse
19 637x468 pixels images of natural scenes selected from Barnard's DXC-930 SFU dataset for colour research. In the original dataset each scene is taken under 11 different close light sources. Here scenes under Philips Ultralume were chosen. Among chosen scenes 17 images contain flat varied in colour sheets of paper (so-called "mondrians"), 5 images contain volumetric objects without or with insignificant highlights, on 2 more images volumetric objects with highlights and inter-reflection effects are depicted. For all images linear contrast adjustment with 95% quantile was applied, 5% of pixels were allowed to be saturated.
The second and the third parts of the dataset consist of natural scene images taken at IITP RAS. There are 5 about 450x500 images of scenes with close light source and 7 1280x1024 images of scenes with diffuse light source . The camera model for IITP-close is unfortunatelly unknown. Images from IITP-diffuse sub-dataset was taken with Olympus D600L camera. All images contain volumetric objects, some of which with highlights, but with no inter-reflection effects.
For annotation purposes, images were first automatically splitted into small subregions with guaranteed colour constancy, and then are manually merged if their colours were undistinguished by a human eye. Segments containing less than 20 pixels were not annotated. In addition, annotations for regions corresponding to deep shadows (i.e. with average brightness close to zero) were provided. Such regions appears at Selected-SFU images containing volumetric objects. Information about colour in such regions is lost and can not be recovered. Annotation for each shadow segment is provided as a separate binary mask.
The dataset is licensed under Apache 2.0, quoted below.
Copyright 2018 Visillect Service LLC
Developed for Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences (IITP RAS)
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
If you use this dataset, please, cite our paper
@inproceedings{smagina2019linear,
title={Linear colour segmentation revisited},
author={Smagina, Anna and Bozhkova, Valentina and Gladilin, Sergey and Nikolaev, Dmitry},
booktitle={Eleventh International Conference on Machine Vision (ICMV 2018)},
volume={11041},
pages={110410F},
year={2019},
organization={International Society for Optics and Photonics}
}
For Selected-SFU subdataset, please, cite also
@article{barnard2002data,
title={A data set for color research},
author={Barnard, Kobus and Martin, Lindsay and Funt, Brian and Coath, Adam},
journal={Color Research \& Application: Endorsed by Inter-Society Color Council, The Colour Group (Great Britain), Canadian Society for Color, Color Science Association of Japan, Dutch Society for the Study of Color, The Swedish Colour Centre Foundation, Colour Society of Australia, Centre Fran{\c{c}}ais de la Couleur},
volume={27},
number={3},
pages={147--151},
year={2002},
publisher={Wiley Online Library}
}
Thanks to Dr. Pavel Chochia for dataset images collected at IITP RAS.
Sincere gratitude to Dmitry Sidorchuk for technical help.