基于YOLOv3模型的人脸检测与头部姿态估计融合算法Fusion Algorithm of Face Detection and Head Pose Estimation Based on YOLOv3 Model
李永杰;周桂红;刘博;
摘要(Abstract)：
针对头部姿态估计中的人脸检测框尺寸难于学习问题和将人脸检测、头部姿态估计分为两阶段的模型中流程复杂、耦合程度高、误差累积严重的问题，本文提出一种基于YOLOv3模型的人脸检测与头部姿态估计融合算法。通过K-means聚类方法对训练集中人脸区域的尺寸进行聚类，得出9组聚类结果，以模拟真实情况下人脸区域的尺寸和比例；通过拓展YOLOv3模型，实现人脸检测和头部姿态估计同时进行，并在3个不同层次的特征图上进行人脸检测和头部姿态估计，实现对特征图的多尺度检测，充分利用了特征图中的信息；采用端到端模式进行训练，简化头部姿态估计任务的处理流程。在CAS-PEAL-R1姿态子集上取得99.23%的预测准确率，在Pointing′04数据集上pitch和yaw方向分别取得了3.79°和4.24°的平均绝对误差。结果表明，本模型在满足实时性要求的前提下，能够出色完成人脸区域检测与头部姿态估计任务，充分证实本文方法的可靠性与实用性。
关键词(KeyWords)： 头部姿态估计;YOLOv3模型;K-means;多尺度检测;深度学习
基金项目(Foundation): 国家自然科学基金(61972132)
作者(Authors): 李永杰;周桂红;刘博;
DOI: 10.16088/j.issn.1001-6600.2021070911
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