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
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