Can Salient Interest Regions Resume Emotional Impact of an Image?

The salient regions of interest are supposed to contain the interesting keypoints for analysis and understanding. We studied in this paper the impact of image reduction to the region of interest on the emotion recognition. We chose a bottom-up visual attention model because we addressed emotions on a new low-semantic data set SENSE Studies of Emotion on Natural image databaSE. We organized two experimentations. The first one has been conducted on the whole images called SENSE1 and the second on reduced images named SENSE2. These latter are obtained with a visual attention model and their size varies from 3% to 100% of the size of the original ones. The information collected during these evaluations are the nature and the power of emotions. For the nature observers have choice between "Negative", "Neutral" and "Positive" and the power varies from "Weak" to "Strong". On the both experimentations some images have ambiguous categorization. In fact, the participants were not able to decide on their emotional class Negative, Neutral ans Positive. The evaluations on reduced images showed that average 79% of the uncategorised images during SENSE1 are categorized during SENSE2 in one of the both major classes. Reducing the size of the area to be observed leads to a better evaluation maybe because some semantic content are attenuated.