28-10-2014, 11:56 AM
Abstracts: The accuracy of face alignment affects the performance of a face recognition system. Since face alignment is usually conducted using eye positions, an accurate eye localization algorithm is therefore essential for accurate face recognition. In this project, we first study the impact of eye locations on face recognition accuracy, and then introduce an automatic technique for eye detection. The validation shows that our eye detector has an overall 94.5 % eye detection rate, with the detected eyes very close to the manually provided eye positions. In addition, the face recognition performance based on the automatic eye detection is shown to be comparable to that of using manually given eye positions. "Face Recognition" generally involves two stages: 1. Face Detection, where a photo is searched to find any face (shown here as a green rectangle), then image processing cleans up the facial image for easier recognition. 2. Face Recognition, where that detected and processed face is compared to a database of known faces, to decide who that person is.