PT Unknown
AU Marc Serra
   Olivier Penacchio
   Robert Benavente
   Maria Vanrell
TI Names and Shades of Color for Intrinsic Image Estimation
BT 25th IEEE Conference on Computer Vision and Pattern Recognition
PY 2012
BP 278
EP 285
DI 10.1109/CVPR.2012.6247686
AB In the last years, intrinsic image decomposition has gained attention. Most of the state-of-the-art methods are based on the assumption that reflectance changes come along with strong image edges. Recently, user intervention in the recovery problem has proved to be a remarkable source of improvement. In this paper, we propose a novel approach that aims to overcome the shortcomings of pure edge-based methods by introducing strong surface descriptors, such as the color-name descriptor which introduces high-level considerations resembling top-down intervention. We also use a second surface descriptor, termed color-shade, which allows us to include physical considerations derived from the image formation model capturing gradual color surface variations. Both color cues are combined by means of a Markov Random Field. The method is quantitatively tested on the MIT ground truth dataset using different error metrics, achieving state-of-the-art performance.
ER