Modeling perspective effects in photographic composition

Automatic understanding of photo composition is a valuable technology in multiple areas including digital photography, multimedia advertising, entertainment, and image retrieval. In this paper, we propose a method to model geometrically the compositional effects of linear perspective. Comparing with existing methods which have focused on basic rules of design such as simplicity, visual balance, golden ratio, and the rule of thirds, our new quantitative model is more comprehensive whenever perspective is relevant. We first develop a new hierarchical segmentation algorithm that in-tegrates classic photometric cues with a new geometric cue inspired by perspective geometry. We then show how these cues can be used directly to detect the dominant vanish-ing point in an image without extracting any line segments, a technique with implications for multimedia applications beyond this work. Finally, we demonstrate an interesting application of the proposed method for providing on-site composition feedback through an image retrieval system.