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.
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Text Reference
David, Martin, Charless, Fowlkes, and Jitendra Malik. Learning to detect natural image boundaries using brightness and texture. In Advances in Neural Information Processing Systems. 2002.BibTeX Reference
@inproceedings{MartinFM_NIPS_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"
}