Review on Clinical Depression Detection using Face and Upper Body Part
Human emotions are an important part of our life. We express our feelings through emotions .When a person is
sad, then the person cause a stress. But when that stress prolongs more than a week then such a condition called as a
“Depression”. Depression is caused due to the people live at fast life structure and cause pressure in their workplace, family
etc. Depression is one type of mental illness. Depression is a common mental illness with a prevalence of 10 to 15% in
population. Now it seems to be a common type of problem in most of the person. Hence to detect the depression state in
human being, there is need to develop some tools which can detect the depression in human. This survey paper describes
different algorithms and methods which will help to detect the depression phase in human by face recognition. This paper
specifically gives the methods for recognition of face, classification techniques for detection of different face parts like eyes,
lips etc. By using this techniques and algorithm one can collect the data base for depression analysis. Hence with the help of
techniques and algorithms described in paper ,It is easy to detect the depression without the physical presence of doctors.
Also papers describes the automatic depression detection in adolescents.
Index Terms - Clinical Depression, Face detection, KNN: K Nearest Neighbor, LBP : Local Binary Pattern, Tanaka and
gauss Newton point, curvlet transform, FACS ,Eigenface, fisherface, principal component analysis (PCA) ,Linear
descriminant analysis (LDA), Adolescnts.