Open AccessRules of photography for image memorability analysis
Author(s) -
Lahrache Souad,
El Ouazzani Rajae,
El Qadi Abderrahim
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.0631
Subject(s) - computer science , photography , image (mathematics) , digital photography , digital image , artificial intelligence , task (project management) , the internet , computer vision , internet of things , information retrieval , image processing , world wide web , art , visual arts , management , economics
Photos are becoming more spread with digital age. Cameras, smart phones and Internet provide large dataset of images available to a wide audience. Assessing memorability of these photos is becoming a challenging task. Besides, finding the best representative model for memorable images will enable memorability prediction. The authors develop a new approach‐based rule of photography to evaluate image memorability. In fact, they use three groups of features: image basic features, layout features and image composition features. In addition, they introduce a diversified panel of classifiers based on some data mining techniques used for memorability analysis. They experiment their proposed approach and they compare its results to the state‐of‐the‐art approaches dealing with image memorability. Their approach experiment's results prove that models used in their approach are encouraging predictors for image memorability.