Abstract | ||
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In this work we design an adaptive color constancy algorithm that, exploiting the skin regions found in faces, is able to estimate and correct the scene illumination. The algorithm automatically switches from global to spatially varying color correction on the basis of the illuminant estimations on the different faces detected in the image. An extensive comparison with both global and local color constancy algorithms is carried out to validate the effectiveness of the proposed algorithm in terms of both statistical and perceptual significance on a large heterogeneous data set of RAW images containing faces. |
Year | DOI | Venue |
---|---|---|
2014 | 10.1109/TPAMI.2013.2297710 | Pattern Analysis and Machine Intelligence, IEEE Transactions |
Keywords | DocType | Volume |
estimation theory,face recognition,image colour analysis,lighting,object detection,RAW images,adaptive color constancy algorithm,global varying color correction,heterogeneous data set,perceptual significance,scene illumination correction,scene illumination estimation,skin regions,spatial varying color correction,statistical significance,Color constancy,face detection,global illuminant estimation,local illuminant estimation | Journal | 36 |
Issue | ISSN | Citations |
8 | 0162-8828 | 18 |
PageRank | References | Authors |
0.66 | 30 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Simone Bianco | 1 | 226 | 24.48 |
Raimondo Schettini | 2 | 1476 | 154.06 |