Evaluating the Accuracy of Smartphone-Based Photogrammetry and Videogrammetry in Facial Asymmetry Measurement

Facial asymmetry presents a significant challenge for health practitioners, including physicians, dentists, and physical therapists. Manual measurements often lack the precision needed for accurate assessments, highlighting the appeal of imaging technologies like structured light scanners and photogrammetric systems. However, high-end commercial systems remain cost prohibitive, especially for public health services in developing countries. This study aims to evaluate cell-phone-based photogrammetric methods for generating 3D facial models to detect facial asymmetries. For this purpose, 15 patients had their faces scanned with the ACADEMIA 50 3D scanner, as well as with cell phone images and videos using photogrammetry and videogrammetry, resulting in 3D facial models. Each 3D model (coming from a 3D scanner, photogrammetry, and videogrammetry) was half-mirrored to analyze dissimilarities between the two ideally symmetric face sides using Hausdorff distances between the two half-meshes. These distances were statistically analyzed through various measures and hypothesis tests. The results indicate that, in most cases, both photogrammetric and videogrammetric approaches are as reliable as 3D scanning for detecting facial asymmetries. The benefits and limitations of using images, videos, and 3D scanning are also presented.