Mañana, JUEVES, 24 DE ABRIL, el sistema se apagará debido a tareas habituales de mantenimiento a partir de las 9 de la mañana. Lamentamos las molestias.
Analysing facial regions for face recognition using forensic protocols
Entity
UAM. Departamento de Tecnología Electrónica y de las ComunicacionesPublisher
Springer Berlin HeidelbergDate
2013-08Citation
10.1007/978-3-642-38061-7_22
Highlights on Practical Applications of Agents and Multi-Agent Systems: International Workshops of PAAMS. Communications in Computer and Information Science, Volumen 365. Springer, 2013. 223-230.
ISSN
1865-0929ISBN
978-3-642-38060-0 (print); 978-3-642-38061-7 (online)DOI
10.1007/978-3-642-38061-7_22Funded by
This work has been partially supported by contract with Spanish Guardia Civil and projects BBfor2 (FP7-ITN-238803), Bio-Challenge (TEC2009-11186), Bio-Shield (TEC2012-34881), Contexts (S2009/TIC-1485), TeraSense (CSD2008-00068) and "Cátedra UAM-Telefónica".Project
info:eu-repo/grantAgreement/EC/FP7/238803; Comunidad de Madrid. S2009/TIC-1485/CONTEXTSEditor's Version
http://dx.doi.org/10.1007/978-3-642-38061-7_22Subjects
Forensic; Biometrics; Face recognition; Facial regions; Forensic casework; TelecomunicacionesNote
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-38061-7_22Proceedings of International Workshops of Practical Applications of Agents and Multi-Agent Systems (PAAMS), held in 2013, Salamanca (Spain).
Rights
© Springer-Verlag Berlin Heidelberg 2013Abstract
This paper focuses on the analysis of automatic facial regions extraction for face recognition applications. Traditional face recognition systems compare just full face images in order to estimate the identity, here different facial areas of face images obtained from both uncontrolled and controlled environments are extracted from a person image. In this work, we study and compare the discriminative capabilities of 15 facial regions considered in forensic practice such as full face, nose, eye, eyebrow, mouth, etc. This study is of interest to biometrics because a more robust general-purpose face recognition system can be built by fusing the similarity scores obtained from the comparison of different individual parts of the face. To analyse the discriminative power of each facial region, we have randomly defined three population subsets of 200 European subjects (male, female and mixed) from MORPH database. First facial landmarks are automatically located, checked and corrected and then 15 forensic facial regions are extracted and considered for the study. In all cases, the performance of the full face (faceISOV region) is higher than the one achieved for the rest of facial regions. It is very interesting to note that the nose region has a very significant discrimination efficiency by itself and similar to the full face performance.
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Google Scholar:Tomé González, Pedro
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Vera Rodríguez, Rubén
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Fiérrez Aguilar, Julián
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