Joint People Recognition across Photo Collections Using Sparse Markov Random Fields

  • Markus Brenner
  • Ebroul Izquierdo
Conference paper

DOI: 10.1007/978-3-319-04114-8_29

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8325)
Cite this paper as:
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

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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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Markus Brenner
    • 1
  • Ebroul Izquierdo
    • 1
  1. 1.School of EECSQueen Mary University of LondonUK

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