Automatic head and facial feature extraction based on geometry variations

Facial anthropometry plays an important role in ergonomic applications. Most ergonomically designed products depend on stable and accurate human body measurement data. Our research automatically identifies human facial features based on three-dimensional geometric relationships, revealing a total of 67 feature points and 24 feature lines — more than the definitions associated with MPEG-4. In this study, we also verify the replicability, robustness, and accuracy of this feature set. Even with a lower-density point cloud from a non-dedicated head scanner, this method can provide robust results, with 86.6% validity in the 5 mm range. We also analyze the main 31 feature points on the human face, with 96.7% validity of less than 5 mm.

► A geometry-based method for automatically identifying three-dimensional facial features. ► 67 feature points and 24 feature lines are mathematically defined and demonstrated. ► Over 80% of the total 67 features meet the 5 mm assessment standard. ► Average 96.7% of the main 31 features’ replicability satisfies the 5 mm standard. ► Over 90% of the total 67 features’ accuracy was within 5 mm.