Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/46132
Título: | Linking face images captured from the optical phenomenon in the wild for forensic science | Autores/as: | Das, Abhijit Sengupta, Abira Ferrer, Miguel A. Pal, Umapada Blumenstein, Michael |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | Face recognition Image capture Training Forensics Reflection, et al. |
Fecha de publicación: | 2018 | Editor/a: | Institute of Electrical and Electronics Engineers (IEEE) | Publicación seriada: | IEEE International Conference on Biometrics, Theory, Applications and Systems | Conferencia: | 2017 IEEE International Joint Conference on Biometrics, IJCB 2017 | Resumen: | This paper discusses the possibility of use of some challenging face images scenario captured from optical phenomenon in the wild for forensic purpose towards individual identification. Occluded and under cover face images in surveillance scenario can be collected from its reflection on a surrounding glass or on a smooth wall that is under the coverage of the surveillance camera and such scenario of face images can be linked for forensic purposes. Another similar scenario that can also be used for forensic is the face images of an individual standing behind a transparent glass wall. To investigate the capability of these images for personal identification this study is conducted. This work investigated different types of features employed in the literature to establish individual identification by such degraded face images. Among them, local region based featured worked best. To achieve higher accuracy and better facial features face image were cropped manually along its close bounding box and noise removal was performed (reflection, etc.). In order to experiment we have developed a database considering the above mentioned scenario, which will be publicly available for academic research. Initial investigation substantiates the possibility of using such face images for forensic purpose. | URI: | http://hdl.handle.net/10553/46132 | ISBN: | 978-1-5386-1125-8 | ISSN: | 2474-9699 | DOI: | 10.1109/BTAS.2017.8272770 | Fuente: | IEEE International Joint Conference on Biometrics, IJCB 2017,v. 2018-January, p. 781-786 |
Colección: | Actas de congresos |
Citas SCOPUSTM
1
actualizado el 24-nov-2024
Visitas
74
actualizado el 09-mar-2024
Google ScholarTM
Verifica
Altmetric
Comparte
Exporta metadatos
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.