Paper Info
Title
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.
Year
DOI
Venue
2009
10.1007/978-3-642-04146-4_57
ICIAP
Keywords
Field
DocType
achieved result,red eye artifact,automatic detection,red eye candidate,acquired image,bag-of-keypoints classification,bag-of-keypoints paradigm,red eye detection,digital photography,red eye,non-professional photography
Computer vision,Scale-invariant feature transform,Digital photography,GLOH,Pattern recognition,Red eye,Computer science,Support vector machine,Photography,Artificial intelligence
Conference
Volume
ISSN
Citations 
5716
0302-9743
2
PageRank 
References 
Authors
0.40
17
4
Name
Order
Citations
PageRank
Sebastiano Battiato165978.73
Mirko Guarnera2536.59
Tony Meccio3131.27
Messina, G.415913.42