A Robust Two Stage Approach for Eye Detection
This paper adopts face localization to eye extraction strategy for eye detection in complex scenes. First, an energy analysis is applied to enhance face localization performance by removing most noise-like regions rapidly. According to anthropometry, the face-of-interest (FOI) region is located using signatures derived from the proposed head contour detection (HCD) approach that searches the best combinations of facial sides and head contours. Second, via the de-edging preprocessing for facial sides, a wavelet subband inter-orientation projection method is devised to generate and select eye-like candidates. By utilizing the geometric discrimination information among the facial components, such as the eyes, nose, and mouth, the proposed eye verification rules verify the eye pair selected from the candidates. The experimental results demonstrate the significance performance improvement using the proposed method over others on three head-and-shoulder databases.