Aesthetic feature design and aesthetic quality assessment for group photograph

Image aesthetics quality assessment has received extensive research in recent years, but there are still few studies on the aesthetic quality evaluation of group photograph of humans. In this work, we designed a set of high-level aesthetic features based on the experience and principles of group photography, including opened-eye, gaze, smile, facial occluded, facial orientation, facial blur, character center. Then we combined them and 83 generic aesthetic features to build two aesthetic assessment models. A large dataset of group photographs - GPD- annotated with the aesthetic score was constructed. The experimental result on the GPD shows that our features perform well for categorizing professional photos and snapshots and predicting the distinction of multiple group photographs of diverse human states under the same scene.The classification accuracy reached 70.97%, the discrimination metric we proposed reached 1.368, which was higher than the negative discrimination value of other methods.