Red Eye Detection through Bag-of-Keypoints Classification

Abstract. Red eye artifacts are a well-known problem in digital photography. Small compact devices and point-and-click usage, typical of non-professional photography, greatly increase the likelihood for red eyes to appear in acquired images. Automatic detection of red eyes is a very challenging task, due to the variability of the phenomenon and the general difficulty in reliably discerning the shape of eyes. This paper presents a method for discriminating between red eyes and other objects in a set of red eye candidates. The proposed method performs feature-based image analysis and classification just considering the bag-of-keypoints paradigm. Experiments involving different keypoint detectors/descriptors are performed. Achieved results are presented, as well as directions for future work.

• Type: Conference
• Year: 2009
• Where: ICIAP
• Authors: Sebastiano Battiato, Mirko Guarnera, Tony Meccio, Giuseppe Messina
• Keywords: ICIAP 2009, Image Processing, Red Eye Artifacts, Red Eye Candidates, Red Eyes