Fast and precise iris localization is a vital technique for face recognition, eye tracking, and gaze estimation. Low-resolution images bring about great difficulties for locating the iris precisely by traditional methods. In this paper, a fast and robust method to precisely detect the position and contour of the irises in low-resolution facial images is presented. A three-step coarse-to-fine strategy is employed. First, a gradient integral projection function is proposed to roughly detect the eye region, and the vertical integral projection function is adopted to select several possible vertical boundaries of the irises. Second, we have proposed a novel rectangular integro-variance operator to precisely locate both of the irises. Finally, the localization results are verified by two simple heuristic rules. A novel and more rigorous criterion is also proposed to evaluate the performance of the algorithm. Comparison experiments on images from the FERET and the Extended YaleB databases demonstrate that our method is more robust than traditional methods to scale variation, illumination changes, part occlusion, and limited changes of head poses in low-resolution facial images.