Non-intrusive practitioner pupil detection for unmodified microscope oculars

Modern microsurgery is a long and complex task requiring the surgeon to handle multiple microscope control: while performing the surgery. Eye tracking provides an additional means of interaction for the surgeon that could be used to alleviate this situation, diminishing surgeon fatigue and surgery time, thus decreasing risks o: infection and human error. In this paper, we introduce a novel algorithm for pupil detection tailored for eye images acquired through an unmodified microscope ocular. The proposed approach, the Hough transform, an six state-of-the-art pupil detection algorithms were evaluated on over 4000 hand-labeled images acquired from a digital operating microscope with a non-intrusive monitoring system for the surgeon eyes integrated. Our results show that the proposed method reaches detection rates up to 71% for an error of approximate to 3% w.r.t the input image diagonal; none of the state-of-the-art pupil detection algorithms performed satisfactorily. The algorithm and hand-labeled data set can be downloaded at:: www.ti.uni-tuebingen.de/perception.