Scenario-based score fusion for face recognition at a distance
EntityUAM. Departamento de Tecnología Electrónica y de las Comunicaciones
10.1109/CVPRW.2010.55432312010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, 2010. 67 - 73
Funded byThis work has been partially supported by projects Bio-Challenge (TEC2009-11186), Contexts (S2009/TIC-1485), TeraSense (CSD2008-00068) and "Cátedra UAM-Telefónica".
ProjectComunidad de Madrid. S2009/TIC-1485/CONTEXTS
SubjectsGaussian processes; Discrete cosine transforms; Face recognition; Image fusion; Principal component analysis; Support vector machines; Telecomunicaciones
NotePersonal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. P. Tomé, J. Fiérrez, F. Alonso-Fernández, J. Ortega-García, "Scenario-based score fusion for face recognition at a distance" in Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), San Francisco, (CA), 2010, pp. 67 - 73
Rights© 2010 IEEE
The effect of different acquisition distances on the performance of face verification is studied. In particular, we evaluate two standard approaches using popular features (DCT and PCA) and matchers (GMM and SVM) under variation in the acquisition distance, as well as their score-level combination. The DCT-GMM-based system is found to be more robust to acquisition distance degradation than the PCA-SVM-based system. We exploit this fact by introducing an adaptive score fusion scheme based on a novel automatic scenario estimation which is shown to improve our system in uncontrolled environments.
Google Scholar:Tomé González, Pedro - Fiérrez Aguilar, Julián - Alonso Fernández, Fernando - Ortega García, Javier
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Face recognition at a distance: Scenario analysis and applications
Acquisition scenario analysis for face recognition at a distance
Benchmarking quality-dependent and cost-sensitive score-level multimodal biometric fusion algorithms Poh, Norman; Bourlai, Thirimachos; Kittler, Josef; Allano, Lorène; Alonso Fernández, Fernando; Ambekar, Onkar; Baker, John P.; Dorizzi, Bernadette; Fatukasi, Omolara; Fiérrez Aguilar, Julián; Ganster, Harald; Ortega García, Javier; Maurer, Donald E.; Salah, Albert Ali; Scheidat, Tobias; Vielhauer, Claus