Research on depression detection method based on facial action unit
ZHAO Junkai
GAO Hongxiang
ZHAO Lulu
CHAI Xuefeng
WANG Pengcheng
LI Jianqing
LIU Chengyu
Abstract：In order to solve the problem that the depression diagnosis in medical practice is complicated and depends on the sub-jective judgment and experience accumulation of doctors,we proposed a depression detection system based on facial action unit by u-sing computer algorithm,which expanded the range of facial image recognition and introduced expert prior knowledge.The output re-sults of the face detection model and the key point detection model were encoded into the depression detection model by setting the seg-mentation rules of the facial action unit.Finally,each face image was divided into regions,which could achieve facial action unit recog-nition of local regions of the face at a finer granularity,thereby achieving higher accuracy and improving the accuracy of depression de-tection.This study can provide a new idea for depression detection based on facial action unit,which has important research signifi-cance.
Keywords：Depression detectionFacial action unitAffective computingKey point detectionSegmentation rules
Publication Date：2024-10-28
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：7( 349-355 )