Accurate eye localization in low and standard definition content

In this paper we address the problem of eye localization in low and standard definition content, such as webcam- generated and TV images. We present a probabilistic eye localization method based on well-known multiscale local binary patterns (LBPs), which provide a simple and pow- erful spatial description of texture, and are robust to the noise typical to low and standard definition content. Our primary contribution is in the proposed method of combin- ing the LBPs that is targeted towards achieving spatial ac- curacy under mentioned conditions. Evaluation performed on a standard dataset of webcam-quality images shows that our approach has superior performance with respect to the state of the art, while having a reasonable complexity and a low memory footprint.