Face recognition at a distance: Scenario analysis and applications
EntityUAM. Departamento de Tecnología Electrónica y de las Comunicaciones
PublisherSpringer Berlin Heidelberg
10.1007/978-3-642-14883-5_44Distributed Computing and Artificial Intelligence: 7th International Symposium. Advances in Intelligent and Soft Computing, Volumen 79. Springer, 2010. 341-348
ISBN978-3-642-14882-8 (print); 978-3-642-14883-5 (online)
Funded byThis work has been supported by project Contexts (S2009/TIC-1485).
ProjectComunidad de Madrid. S2009/TIC-1485/CONTEXTS
SubjectsComputational Intelligence; Artificial Intelligence; Robotics; Telecomunicaciones
NoteThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-14883-5_44
Proceedings of the International Symposium of Distributed Computing and Artificial Intelligence held in Valencia (Spain).
Rights© Springer-Verlag Berlin Heidelberg 2010
Face recognition is the most popular biometric used in applications at a distance, which range from high security scenarios such as border control to others such as video games. This is a very challenging task since there are many varying factors (illumination, pose, expression, etc.) This paper reports an experimental analysis of three acquisition scenarios for face recognition at a distance, namely: close, medium, and far distance between camera and query face, the three of them considering templates enrolled in controlled conditions. These three representative scenarios are studied using data from the NIST Multiple Biometric Grand Challenge, as the first step in order to understand the main variability factors that affect face recognition at a distance based on realistic yet workable and widely available data. The scenario analysis is conducted quantitatively in two ways. First, an analysis of the information content in segmented faces in the different scenarios. Second, an analysis of the performance across scenarios of three matchers, one commercial, and two other standard approaches using popular features (PCA and DCT) and matchers (SVM and GMM). The results show to what extent the acquisition setup impacts on the verification performance of face recognition at a distance.
Google Scholar:Vera Rodríguez, Rubén - Tomé González, Pedro - Ortega García, Javier - Fiérrez Aguilar, Julián
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