连续热图像中人脸区域自动检测的学习数据量研究

Tsuyoshi Takahashi, Bo Wu, Y. Kageyama, M. Nishida, M. Ishii
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引用次数: 0

摘要

脸颊温度的时间变化包含了检测情绪发生的重要信息。为了准确测量面部特定区域的皮肤温度,我们开发了一种基于30fps的连续热图像的人脸检测方法。在本文中,我们研究了足以创建高精度人脸区域检测器的最小学习数据量。5人的实验结果表明,在使用350张以上的图像时,获得了较高的检测率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A study of learning data size for automatic face area detection in sequential thermal images
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.
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