Details

Autor(en) / Beteiligte

• Martin, D.R.
• Fowlkes, C.C.
• Malik, J.

Titel

Learning to detect natural image boundaries using local brightness, color, and texture cues

Ist Teil von

• IEEE transactions on pattern analysis and machine intelligence, 2004-05, Vol.26 (5), p.530-549

Ort / Verlag

United States: IEEE

Erscheinungsjahr

2004

Link zum Volltext

• IEEE_Xplore

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• 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, color, and texture associated with natural boundaries. In order to combine the information from these features in an optimal way, we train a classifier using human labeled images as ground truth. The output of this classifier provides the posterior probability of a boundary at each image location and orientation. We present precision-recall curves showing that the resulting detector significantly outperforms existing approaches. Our two main results are 1) that cue combination can be performed adequately with a simple linear model and 2) that a proper, explicit treatment of texture is required to detect boundaries in natural images.