A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics
Abstract
This paper presents a database containing `ground truth' segmentations
produced by humans for images of a wide variety of natural scenes. We define
an error measure which quantifies the consistency between segmentations of
differing granularities and find that different human segmentations of the
same image are highly consistent. Use of this dataset is demonstrated in two
applications: (1) evaluating the performance of segmentation algorithms and
(2) measuring probability distributions associated with Gestalt grouping
factors as well as statistics of image region properties.
Cite
@inproceedings{a-database-of-human-segmented-natural-images-and-2001,
author = {David Martin and Charless Fowlkes and Doron Tal and Jitendra Malik},
title = {A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics},
booktitle = {ICCV},
pages = {II: 416-423},
year = {2001},
doi = {10.1109/iccv.2001.937655},
url = {https://doi.org/10.1109/iccv.2001.937655},
}