Aging of the face degrades the performance of face recognition algorithms. This paper presents recent work in synthetic age progression as well as performance comparisons for modern face recognition systems. Two top-performing, commercial systems along with a traditional PCA-based face recognizer are compared. It is shown that the commercial systems perform better than the baseline PCA algorithm, but their performance still deteriorates on an aged data-set. It is also shown that the use of our aging model improves the rank-one accuracy in these systems. © Springer-Verlag Berlin Heidelberg 2009.
CITATION STYLE
Sethuram, A., Patterson, E., Ricanek, K., & Rawls, A. (2009). Improvements and performance evaluation concerning synthetic age progression and face recognition affected by adult aging. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5558 LNCS, pp. 62–71). https://doi.org/10.1007/978-3-642-01793-3_7
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