3D virtual reconstruction of human body parts is nowadays a common practice in many research fields such as the medical one, the manufacturing of customized products or the creation of personal avatar for gaming purpose. The acquisition can be performed with the use of an active stereo system (i.e., laser scanner, structured light sensors) or with the use of a passive image-based approach. While the former represents a consolidated approach in human modeling, the second is still an active research field. Usually, the reconstruction of a body part through a scanning system is expensive and requests to project light on the patient’s body. On the other hand, the image-based approach could use multi-photo technique to reconstruct a real scene and provides some advantages: low equipment costs (only one camera) and rapid acquisition process of the photo set. In this work, the use of the photogrammetry approach for the reconstruction of humans’ face has been investigated as an alternative to active scanning systems. Two different photogrammetric approaches have been tested to verify their potentiality and their sensitivity to configuration parameters. An initial comparison among them has been performed, considering the overall number of points detected (sparse point cloud reconstruction, dense point cloud reconstruction). Besides, to evaluate the accuracy of the reconstruction, a set of measures used in the design of wearable head-related products has been assessed
