Identifying and Describing Facial Features of a Human Figure Drawing Test (HFDT) towards House-Tree-Person Test (HTP)

Abstract — The purpose of this research is to start a study that would eventually create a framework that would be a guide in the administration and interpretation of HFDT. In this paper, the Researchers proposed a model using Cascade object detectors and the Viola Jones algorithm. This model would identify and describe the facial features of human sketch from the human figure drawing test (HFDT) based on the image dataset that the researchers gathered through random sampling. The accuracy for facial feature identification and description were 31% and 35% respectively after the first test. After adjustments were made, Identification accuracy went up to 86% and Description accuracy went up to 82%. This paper will also discuss on how this model can be improved further.