P212 - BIOSIG 2013 - Proceedings of the 12th International Conference of the Biometrics Special Interest Group

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Konferenzbeitrag
Combination of facial landmarks for robust eye localization using the discriminative generalized Hough transform
(BIOSIG 2013, 2013) Hahmann, Ferdinand; Böer, Gordon; Schramm, Hauke
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.