A Hybrid Approach for Eye Localization in Video

Eye Localization is a preprocessing step for operations such as orientation correction and scaling required in face recognition problem. The success of facial feature analysis and face recognition system depends on eye position detected and the other facial features estimated on this. This paper presents a hybrid approach for eye localization in a video which integrates efficiency of a feature based approach and accuracy of an appearance based approach. In particular, the proposed approach combines Line Edge Map (feature based) approach and Bayesian Classifier (appearance based) approach. The experiments have been carried out on videos of people in normal blink as well as in sleepy condition. The performance of proposed algorithm has been validated on various non-parametric tests.