Abstract
Face recognition systems based on elastic graph matching work by comparing the positions and image neighborhoods of a number of detected feature points on faces in input images with those in a database of pre-registered face templates. Such systems can absorb a degree of deformation of input faces due for example to facial expression, but may generate recognition errors if the deformation becomes significantly large. We show that, somewhat counter-intuitively, robustness to facial expressions can be increased by applying random perturbations to the positions of feature points in the database of face templates. We present experimental results on video sequences of people smiling and talking, and discuss the probable origin of the observed effect.
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© 2003 Springer-Verlag Berlin Heidelberg
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Clippingdale, S., Fujii, M. (2003). Face Recognition for Video Indexing: Randomization of Face Templates Improves Robustness to Facial Expression. In: GarcÃa, N., Salgado, L., MartÃnez, J.M. (eds) Visual Content Processing and Representation. VLBV 2003. Lecture Notes in Computer Science, vol 2849. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39798-4_7
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DOI: https://doi.org/10.1007/978-3-540-39798-4_7
Publisher Name: Springer, Berlin, Heidelberg
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