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

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 Error（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.

Key words: face age estimation, feature extraction algorithm, convolutional neural network, characteristic channel weight assignment, multiscale feature regression