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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Acquisition Scenario Analysis for Face Recognition at a Distance
verfasst von : P. Tome, J. Fierrez, M. C. Fairhurst, J. Ortega-Garcia
Erschienen in: Advances in Visual Computing
Verlag: Springer Berlin Heidelberg
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An experimental analysis of three acquisition scenarios for face recognition at a distance is reported, 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, we analyze the information content in segmented faces in the different scenarios. Second, we analyze 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.