Saliency of color image derivatives: a comparison between computational models and human perception.
In this paper, computational methods are proposed to compute color edge saliency based on the information content of color edges. The computational methods are evaluated on bottom-up saliency in a psychophysical experiment, and on a more complex task of salient object detection in real-world images. The psychophysical experiment demonstrates the relevance of using information theory as a saliency processing model and that the proposed methods are significantly better in predicting color saliency (with a human-method correspondence up to 74.75% and an observer agreement of 86.8%) than state-of-the-art models. Furthermore, results from salient object detection confirm that an early fusion of color and contrast provide accurate performance to compute visual saliency with a hit rate up to 95.2%.
Vazquez
Eduard
E
Computer Vision Center, Universitat Autónoma de Barcelona, 08193 Cerdanyola del Valles, Barcelona, Spain. eduard.vazquez@cvc.uab.cat
Gevers
Theo
T
Lucassen
Marcel
M
van de Weijer
Joost
J
Baldrich
Ramon
R
D000465:Algorithms; D055253:Color Vision / Q000502:physiology*; D003124:Colorimetry / Q000379:methods*; D003198:Computer Simulation; D005556:Form Perception / Q000502:physiology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity