Authors:
Ashwinee Mehta
1
;
Maged Abdelaal
2
;
Moamen Sheba
2
and
Nic Herndon
1
Affiliations:
1
Department of Computer Science, East Carolina University, Greenville, U.S.A.
;
2
School of Dental Medicine, East Carolina University, Greenville, U.S.A.
Keyword(s):
Similar, non-Collapsed Face, Face Recognition, Classification, Collapsed Face, Reconstruction.
Abstract:
Face recognition is the ability to recognize a person’s face in a digital image. Common uses of face recognition include identity verification, automatically organizing raw photo libraries by person, tracking a specific person, counting unique people and finding people with similar appearances. However, there is no systematic and accurate study for finding a similar non-collapsed face to a given collapsed face. In this paper we focus on the use case of finding people with similar appearances that will help us to find a similar face without a collapse to a collapsed face for dental reconstruction. We used Python’s Open-CV for age and gender classification and face recognition for finding similar faces. Our results provide a set of similar images that can be used for reconstructing the collapsed faces for creating dentures. Thus with the help of a similar non-collapsed face, we can reconstruct a collapsed face for designing effective dentures.