Comparative analysis of eyes detection on face thermal images

This paper presents the evaluation of visual features for the proposed two eye detection method applied to thermal images. The use of two eye region is due to its distinctive pattern and to overcome the issue of blurred and noisy characteristic in the thermal image. Comparative performance analysis on three different features which includes Haar, Histogram of Oriented Gradients (HoG) and Local Binary Patterns (LBP) is conducted. The performance of the eyes detection method is measured based on the correct detection of both eyes inside the face image. The experiments were done on the Natural Visible and Infrared Facial Expression Database (NVIE). The method proposed in this paper shows good eye detection accuracy. The best detection accuracy is obtained using the HoG feature.