Abstract: Eight extended feature prototypes were presented by combining rectangular feature blocks and triangular feature blocks. In consideration of the fact that the amount of eye image blocks is far less than that of non-eye image blocks during a scanning block passing through face images, a fast eye location detection scheme based on AdaBoost algorithm combining rectangular feature blocks and triangular feature blocks was proposed. After most of non-eye blocks are excluded through the foregoing strong classifiers, most eye image blocks and a few of non-eye image blocks are detected through the rear parts of the cascade classifier, which can reduce the detection time and boost the detection speed. The experiments further show that the scheme has better detection performance and positive detection rate compared to the case only employed Haar features.