OBJECTIVES: A new, low-cost photogrammetric method has been developed for facial morphometry applications. To evaluate the system, tests for the measurement and comparison of three-dimensional virtual faces were carried out in different subjects. MATERIALS AND METHODS: Twenty adult white Italian subjects, 10 men and 10 women, of ages ranging from 23 to 37 years, were included in this study. Three cameras were finely calibrated, and the point precision vector length was calculated, together with the quality parameters. For each subject, 3 different acquisitions were performed. A tessellated surface was obtained from each point cloud. The comparison was made by aligning three-dimensional information from different models. Differences between 2 different models were estimated by analysis of the distances. RESULTS: For the cases analyzed, the mean point precision overall root-mean-square vector length was 0.07 mm, with a SD of 0.027 mm. The results are reported for the system's capability of discriminating between the faces of different people. Results of comparisons between facial models of a single person were compared with those of comparisons between different subjects. Student's t-test revealed that the system was able to discriminate among different people, with a P > 95%. Two sex subgroups were formed: the mean error between subgroups ranged from 1.65 to 3.43 mm, and the mean ranged from 1.76 to 2.72 mm. CONCLUSIONS: The experiments confirmed the capabilities and the accuracy of the proposed photogrammetric system. Facial comparison was performed by analysis of distances on three-dimensional virtual models.
OBJECTIVES: A new, low-cost photogrammetric method has been developed for facial morphometry applications. To evaluate the system, tests for the measurement and comparison of three-dimensional virtual faces were carried out in different subjects. MATERIALS AND METHODS: Twenty adult white Italian subjects, 10 men and 10 women, of ages ranging from 23 to 37 years, were included in this study. Three cameras were finely calibrated, and the point precision vector length was calculated, together with the quality parameters. For each subject, 3 different acquisitions were performed. A tessellated surface was obtained from each point cloud. The comparison was made by aligning three-dimensional information from different models. Differences between 2 different models were estimated by analysis of the distances. RESULTS: For the cases analyzed, the mean point precision overall root-mean-square vector length was 0.07 mm, with a SD of 0.027 mm. The results are reported for the system's capability of discriminating between the faces of different people. Results of comparisons between facial models of a single person were compared with those of comparisons between different subjects. Student's t-test revealed that the system was able to discriminate among different people, with a P > 95%. Two sex subgroups were formed: the mean error between subgroups ranged from 1.65 to 3.43 mm, and the mean ranged from 1.76 to 2.72 mm. CONCLUSIONS: The experiments confirmed the capabilities and the accuracy of the proposed photogrammetric system. Facial comparison was performed by analysis of distances on three-dimensional virtual models.
Authors: Luigi Maria Galantucci; Eliana Di Gioia; Fulvio Lavecchia; Gianluca Percoco Journal: Med Biol Eng Comput Date: 2014-04-12 Impact factor: 2.602
Authors: M L Menéndez López-Mateos; J Carreño-Carreño; J C Palma; J A Alarcón; C Menéndez López-Mateos; M Menéndez-Núñez Journal: BMC Oral Health Date: 2019-08-28 Impact factor: 2.757