Eye Location using Hierarchical Classifier

The eyes are important facial landmarks, both for image normalization due to their relatively constant interocular distance, and for post processing due to their anchoring model-based schemes. In this paper a hierarchical classifier for precise eye location algorithm is introduced. The new algorithm involves three main steps. First, a classifier based on AdaBoost algorithm is introduced to locate eye pair roughly. In order to get a reliable location, simple eye location is also introduced for checking the located results. Second, a precise eye location method based on Minimum Extreme Region (MER) is employed to detect eye candidates. Finally, a combine processing based on the above two results is used for the last location. The algorithm is tested on database CAS-PEAL, JAFFE and BioID. The results prove the merit of this approach.