System overview.

Abstract

<p>First, the sample data are divided into equal three parts according to the image complexity (IC). The EEG data induced by high-, medium-, and low-complexity images. We trained the classifiers separately on the different data sets. During testing, we first determined the complexity and category (high-, medium-, or low-complexity image) of the test picture. Then, we calculated the interest scores of the EEG induced by a test image using the corresponding classifier. The result was combined with a certain weight to obtain the final decision score (The image is similar but not identical to the original image, and is therefore for illustrative purposes only).</p