Joint People Recognition across Photo Collections Using Sparse Markov Random Fields

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.