  A new high-precision eye-tracking method has been demonstrated recently by
tracking the motion of iris features rather than by exploiting pupil edges.
While the method provides high precision, it suffers from temporal drift, an
inability to track across blinks, and loss of texture matches in the presence
of motion blur. In this work, we present a new methodology $pi_t$ to address
these issues by optimally combining the information from both iris textures and
pupil edges. With this method, we show an improvement in precision (S2S-RMS &
STD) of at least 48% and 10% respectively while fixating a series of small
targets and following a smoothly moving target. Further, we demonstrate the
capability in the identification of microsaccades between targets separated by
0.2-degree.
