Abstract:Head pose classification is widely used for the preprocessing before face recognition and multi-angle problems,because algorithms such as face recognition often require the input image to be a front face. But affected by the COVID-19 pandemic,people wear face masks to protect themselves safely,which covers most areas of the face.This makes some common algorithms that cannot be applied to head pose classification in the new situation.Therefore, this paper established a method HGL to deal with the head pose classification by adopting color texture analysis of images and line portraits.The proposed HGL method combines the Channel of the HSV color space with the face portrait and grayscale image,and trains the CNN to extract features for classification. The evaluation of the MAFA dataset shows that compared with the algorithms based on facial landmark detection and convolutional neural network, the proposed method has achieved better performance.

Keywords:CNN,HGL, MAFA Dataset.

| DOI: 10.17148/IARJSET.2022.9460