计算机工程与应用2019，Vol.55Issue(21)：134-140,7.DOI:10.3778/j.issn.1002-8331.1903-0045
多尺度YOLO人脸年龄估计方法研究
Research on Face Age Estimation Based on Multi-Scale YOLO Model
摘要
Abstract
To improve the accuracy of age estimation in face images, a feature extraction method based on YOLO model is proposed. The idea of multi-scale regression is applied to Convolutional Neural Network(CNN), which improves the ability of extracting small-scale targets by multi-scale convolution. Combining the idea of feature channel weighting, the problem of feature information loss in feature extraction operation is improved. A decision tree regression is constructed to obtain age estimation. The Mean Absolute Erro(r MAE)is 3.43 on FG-NET, and the interval matching(AEM)is 62.4% on GROUP dataset. The experimental results show that the face information can be detected more accurately by multi-scale feature regression and channel weight allocation, and a more robust face age estimation model can be established.关键词
人脸年龄估计/特征提取算法/卷积神经网络/特征通道权重分配/多尺度特征回归Key words
face age estimation/feature extraction algorithm/convolutional neural network/characteristic channel weight assignment/multiscale feature regression分类
信息技术与安全科学引用本文复制引用
房国志,孙康瞳..多尺度YOLO人脸年龄估计方法研究[J].计算机工程与应用,2019,55(21):134-140,7.基金项目
国家自然科学基金(No.51277043). （No.51277043）
