<title>Two methods for locating feducial points on three-dimensional scans of the human face</title>

Abstract

The objects captured with three-dimensional scanners are, by themselves, of limited value. The real power of 3D scanning emerges as applications derive useful information from the point clouds. Extracting measurements from 3D human body scans is an important capability for those interested in clothing and equipment design, human factors evaluation, and web commerce, among other applications. In order to be practical, measurement extraction functions must be fast, accurate, and reliable. Automation is critical for processing the large numbers of scans envisioned by most developers. In this paper we report two functions for identifying feducial points (landmarks) on the human face. First, we used a template-matching approach where a predefined template of 34 face landmarks is matched to a head scan using a small subset of the template landmarks. Once the template is in place, interrogating local surface geometry refines landmark location. This approach allows us to locate a large number of landmarks quickly, and, more importantly, it allows us to place important but hard to locate landmarks. In our second approach, we used image-processing methods to locate a small blue dot that has been positioned on the face prior to scanning.