A study of learning data size for automatic face area detection in sequential thermal images

Abstract

Chronological change of temperature on cheeks includes important information to detect an emotion occurrence. To measure the specific region of face skin temperature accurately, we have developed a face detection method from sequential thermal image acquired in 30fps. In this paper, we investigated minimum quantity of learning data that is sufficient to create a high accurate face area detector. The experimental results for five persons showed that high detection rate was obtained when using over 350 images.