In nighttime video surveillance, the image details of far objects are often hard to be identified due to poor illumination conditions while the image regions of near objects may be whitened due to overexposure. To alleviate the two problems simultaneously for nighttime video surveillance, we adopt a new multi-intensity infrared illuminator as a supportive light source to provide multiple illumination levels periodically. By using the illuminator with multiple degrees of illumination power, both far and near objects can be clearly captured. In this thesis, an effective algorithm is developed to pick out high quality human faces from nighttime video sequences. Experiment results show that well exposed face images can be automatically detected and selected for people located at various distances from the camera.