Image orientation detection using low-level features and faces

Correct image orientation is often assumed by common imaging applications such as enhancement, browsing, and retrieval. However, the information provided by camera metadata is often missing or incorrect. In these cases manual correction is required, otherwise the images cannot be correctly processed and displayed. In this work we propose a system which automatically detects the correct orientation of digital photographs. The system exploits the information provided by a face detector and a set of low-level features related to distributions in the image of color and edges. To prove the effectiveness of the proposed approach we evaluated it on two datasets of consumer photographs.