Video based pupil detection techniques are useful for Perceptual user interfaces and human monitoring. Pupil detection plays a vital role in identification systems. This paper presents an algorithm for pupil detection in video images under active infrared (IR) illumination. At first, using a low pass filter the eyelashes are removed. Following, the thresholding process takes place. Using the Otsu's thresholding method, the proper thresholding value is estimated. Then, using the genetic algorithm, filter band width and threshold value are estimated accurately. After the pupil segmentation process, pupil boundary is modelled. The modeling process is based on circular Hough transform. Experimental results show promising performances on eye video images captured in ideal and non-ideal conditions.