Gesellschaft für Informatik e.V.

Lecture Notes in Informatics

BIOSIG 2013 P-212, 27-38 (2013).

Gesellschaft für Informatik, Bonn

Copyright © Gesellschaft für Informatik, Bonn


Combination of facial landmarks for robust eye localization using the discriminative generalized Hough transform

Ferdinand Hahmann , Gordon Böer and Hauke Schramm


The Discriminative Generalized Hough Transform (DGHT) is a general and robust automated object localization method, which has been shown to achieve state-of-the-art success rates in different application areas like medical image analysis and person localization. In this contribution the framework is enhanced by a novel facial landmark combination technique which is theoretically introduced and evaluated for an eye localization task on a public database. The technique applies individually trained DGHT models for the localization of different facial landmarks, combines the obtained Hough spaces into a 3D feature matrix and applies a specifically trained higher-level DGHT model for the final localization based on the given features. In addition to that, the framework is further improved by a task-specific multi-level approach which adjusts the zooming-in strategy with respect to relevant structures and confusable objects. With the new system it was possible to increase the iris localization rate from 96.6\% to 97.9\% on 3830 evaluation images. This result is promising, since the variation of the head pose in the database is quite large and the applied error measure considers the worst of a left and right eye localization attempt.

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Gesellschaft für Informatik, Bonn
ISBN 978-3-88579-606-0

Last changed 12.03.2014 15:18:55