Share Email Print
cover

Proceedings Paper

Eyebrow segmentation using active shape models
Author(s): Karen Hollingsworth; Samuel Clark; Joseph Thompson; Patrick J. Flynn; Kevin W. Bowyer
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Prior research has shown that manually-segmented eyebrows can be used for recognition purposes. However, eyebrow recognition is not as useful without an automated segmentation algorithm. We propose a method to automatically outline the eyebrows in a face using active shape models. We train several models using the images from the Face Recognition Grand Challenge and find that including more landmark points around the eyebrows and including the eyes in the model are beneficial. Our eyebrow active shape model gives a 38.6% improvement over eyebrow segmentation obtained using an open-source face active shape model. When comparing the automatically segmented regions with manual segmentation, we achieve 87% true overlap score with a 12% false overlap score.

Paper Details

Date Published: 31 May 2013
PDF: 8 pages
Proc. SPIE 8712, Biometric and Surveillance Technology for Human and Activity Identification X, 871208 (31 May 2013); doi: 10.1117/12.2017646
Show Author Affiliations
Karen Hollingsworth, Univ. of Notre Dame (United States)
Samuel Clark, Univ. of Notre Dame (United States)
Joseph Thompson, Univ. of Notre Dame (United States)
Patrick J. Flynn, Univ. of Notre Dame (United States)
Kevin W. Bowyer, Univ. of Notre Dame (United States)


Published in SPIE Proceedings Vol. 8712:
Biometric and Surveillance Technology for Human and Activity Identification X
Ioannis Kakadiaris; Walter J. Scheirer; Laurence G. Hassebrook, Editor(s)

© SPIE. Terms of Use
Back to Top