Automatic Landmarking on 2.5D Face Range Images

Abstract

In this paper, we develop an automatic land marking method on face data using 2.5-dimensional (2.5D) range images. Automatic facial land marking is a vital process that could be employed to any face application for analysis, registration and recognition. The research aims to locate facial feature points (the eye corners, the nose tip, the mouth corners, chin etc.) automatically without the intervention of human. Automatic land marking has a number of added advantages over manual land marking, especially if the dataset is large, hence the landmark selection could be more accurate and less time consuming. We also developed an interface to ease the visualization of the land marking process. It has interactive tools which allow the manipulation of threshold values. The threshold values are then analyzed and generalized to best detect and extract important key points or/and regions of facial features. The results of the automatic extracted facial features and candidate landmarks are shown in this paper.