Automatic evaluation of photo aesthetic quality is a challenging problem in multimedia computing. Numerous aesthetic features have been proposed in previous works but the features are extracted solely from the photo under evaluation. In this paper, we explore the use of multiple images, and present the relative features that can be easily computed from any score-based features. We show that evaluation on a group basis can facilitate the quality assessment problem. Although the extraction of the new feature is extremely simple, computationally efficient, and requires no training phase, experimental results validate the effectiveness of the proposed approach.