Abstract
We show how to jointly recognize people across an entire photo collection while considering the specifies of personal photos that often depict multiple people. We devise and explore a sparse but efficient graph design based on a second-order Markov Random Field, and that utilizes a distance-based face description method. Experiments on two datasets demonstrate and validate the effectiveness of our probabilistic approach compared to traditional methods.
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Brenner, M., Izquierdo, E. (2014). Joint People Recognition across Photo Collections Using Sparse Markov Random Fields. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds) MultiMedia Modeling. MMM 2014. Lecture Notes in Computer Science, vol 8325. Springer, Cham. https://doi.org/10.1007/978-3-319-04114-8_29
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DOI: https://doi.org/10.1007/978-3-319-04114-8_29
Publisher Name: Springer, Cham
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