Learning to Detect Natural Image Boundaries Using Brightness and Texture
The goal of this work is to accurately detect and localize boundaries in natural scenes using local image measurements. We formulate features that respond to characteristic changes in brightness and texture associated with natural boundaries. In order to combine the information from these features in an optimal way, a classifier is trained using human labeled images as ground truth. We present precision-recall curves showing that the resulting detector outperforms existing approaches.
Text ReferenceDavid, Martin, Charless, Fowlkes, and Jitendra Malik. Learning to detect natural image boundaries using brightness and texture. In Advances in Neural Information Processing Systems. 2002.
author = "Martin, David, and Fowlkes, Charless, and Malik, Jitendra",
title = "Learning to Detect Natural Image Boundaries Using Brightness and Texture",
booktitle = "Advances in Neural Information Processing Systems",
year = "2002",
tag = "grouping"