Abstract
Weinvestigated the performance of 3 face verification algorithms (Correlation Filters, Individual PCA, FisherFaces) on an image database that was collected by a cell phone camera. Cell phone camera images tend to be of poorer quality and because of their portability, algorithms must deal with scale changes and dynamic outdoor illumination changes. While Individual PCA and FisherFaces focus on the image domain, Correlation Filters work in the frequency domain and offer advantages such as shift-invariance, ability to accommodate in-class image variability and closed form expressions. Results suggest that correlation filters offer better verification performance with this database.
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Qidwai, S., Venkataramani, K., Kumar, B.V.K.V. (2004). Face Authentication from Cell Phone Camera Images with Illumination and Temporal Variations. In: Zhang, D., Jain, A.K. (eds) Biometric Authentication. ICBA 2004. Lecture Notes in Computer Science, vol 3072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25948-0_11
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DOI: https://doi.org/10.1007/978-3-540-25948-0_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22146-3
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