title: Predicting Complexity Perception of Real World Images.
abstract: The aim of this work is to predict the complexity perception of real world images. We propose a new complexity measure where different image features, based on spatial, frequency and color properties are linearly combined. In order to find the optimal set of weighting coefficients we have applied a Particle Swarm Optimization. The optimal linear combination is the one that best fits the subjective data obtained in an experiment where observers evaluate the complexity of real world scenes on a web-based interface. To test the proposed complexity measure we have performed a second experiment on a different database of real world scenes, where the linear combination previously obtained is correlated with the new subjective data. Our complexity measure outperforms not only each single visual feature but also two visual clutter measures frequently used in the literature to predict image complexity. To analyze the usefulness of our proposal, we have also considered two different sets of stimuli composed of real texture images. Tuning the parameters of our measure for this kind of stimuli, we have obtained a linear combination that still outperforms the single measures. In conclusion our measure, properly tuned, can predict complexity perception of different kind of images.
authors.affiliation: Department of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy.|Milan Center for Neuroscience, Milano, Italy.
authors.forename: Silvia Elena
authors.initials: SE
authors.lastname: Corchs
authors.affiliation: Department of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy.|Milan Center for Neuroscience, Milano, Italy.
authors.forename: Gianluigi
authors.initials: G
authors.lastname: Ciocca
authors.affiliation: Department of Psychology, University of Milano-Bicocca, Via dell' Innovazione 10, 20126 Milano, Italy.|Milan Center for Neuroscience, Milano, Italy.
authors.forename: Emanuela
authors.initials: E
authors.lastname: Bricolo
authors.affiliation: Department of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy.|Milan Center for Neuroscience, Milano, Italy.
authors.forename: Francesca
authors.initials: F
authors.lastname: Gasparini
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D010775:Photic Stimulation; D014796:Visual Perception; D055815:Young Adult