Eye-tracking technology is becoming more important and is used widely in various fields such as computer-human interaction, medical rehabilitation, user behaviour analysis, marketing, automotive, training, and entertainment. In this work, we use multiple Web cameras for gaze estimation and improving the estimation accuracy at low cost. We carried out an experiment to verify the gaze estimation variance by considering different number of cameras. The experimental results have shown that the estimation variance did not decrease when the number of cameras increased. However, we found that the camera position affects the accuracy and variance of gaze estimation.