Eye Location using Hierarchical Classifier
Gaofeng Xu, Lei Huang, Changping Liu, Ding Shi-qi · 2007
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.