Experiencing the interestingness concept within and between pictures



Experiencing the interestingness concept within and between pictures

Experiencing the interestingness concept within and between pictures
Research Paper / HVEI 2016 / Feb 2016 / Computer Vision, Machine/Deep Learning/AI

Interestingness is the quantification of the ability of an imageto induce interest in a user. Because defining and interpretinginterestingness remain unclear in the literature, we introduce inthis paper two new notions, intra- and inter-interestingness, andinvestigate a novel set of dedicated experiments.More specifically, we propose four experimental protocols:1/ object ranking with a pre-defined word list, 2/ pair-wise com-parison, 3/ image ranking and 4/ eye-tracking. We take advantageof experimenting on the same dataset to draw potential links be-tween the collected data and to state on the agreement betweensubjects. While we do not evidence a relationship between thelocal (intra) and global (inter) notions of interestingness, we doobserve correlated outputs throughout the different protocols. Be-yond the low or moderate values obtained from inter-rater agree-ment metrics, we point out the experimental reproducibility to ar-gue about the universal nature of the interestingness notions.In addition, we bring deep insights on the relationships be-tween interestingness and 7 other criteria, some of them alreadypointed out in the literature as being linked with interestingness.Unusualness and emotion seem to be the strongest enablers forinterestingness. These insights are highly relevant for future workon modeling.