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Research Article Open Access
This paper is an important milestone towards automatic person authentication. In this work, from a video source, video frames with pose free face is automatically sensed. Then mouth region is localized automatically. Then person identification is done using local binary pattern histogram of mouth region. Person identification performance while using neutral face, smile expression and visual speech are compared. A big custom dataset of 180 videos of 30 persons are used. The result gives the conclusion that for person identification visual speech performs well with F1 score of 0.95, followed by neutral face, 0.93 and then smile expression, 0.87. It also concludes that the mouth component of the face itself is efficient enough to identify persons.
Person identification, Local binary pattern histogram, Neutral, Smile expression, Visual speech, Accuracy, F1 score., Speech pathology,Speech Therapy,Speech Therapy for Children,Speech Therapy for Adults,Speech Therapy Materials,Speech Therapy Exercise,Autism Speech Therapy,Visual Eyes Optometry,Speech and Language pathology,Communicate Speech pathology,Bilingual Speech pathology,Medical Speech pathology,Speech Impediment / speech disorder,Interventional Speech Therapy,Speech and Language Disorders