Abstract
We show how to recognize people in Consumer Photo Collections by employing a graphical model together with a distance-based face description method. To further improve recognition performance, we incorporate context in the form of social semantics. We devise an approach that has a data mining technique at its core to discover and incorporate patterns of groups of people frequently appearing together in photos. We demonstrate the effect of our probabilistic approach through experiments on a dataset that spans nearly ten years.
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Brenner, M., Izquierdo, E. (2013). Mining People’s Appearances to Improve Recognition in Photo Collections. In: Li, S., et al. Advances in Multimedia Modeling. MMM 2013. Lecture Notes in Computer Science, vol 7732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35725-1_17
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DOI: https://doi.org/10.1007/978-3-642-35725-1_17
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