Interestingness is the quantification of the ability of an image to induce interest in a user. Because defining and interpreting interestingness remain unclear in the literature, we introduce in this paper two new notions, intra- and inter-interestingness, and investigate 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 comparison, 3/ image ranking and 4/ eye-tracking. We take advantage of experimenting on the same dataset to draw potential links between
the collected data and to state on the agreement between subjects. While we do not evidence a relationship between the local (intra) and global (inter) notions of interestingness, we do observe correlated outputs throughout the different protocols. Beyond the low or moderate values obtained
from inter-rater agreement metrics, we point out the experimental reproducibility to argue about the universal nature of the interestingness notions.
In addition, we bring deep insights on the relationships between interestingness and 7 other criteria, some of them already pointed
out in the literature as being linked with interestingness. Unusualness and emotion seem to be the strongest enablers for interestingness. These insights are highly relevant for future work on modeling.