**4.1 Probabilistic latent semantic analysis (pLSA)**

It is a popular unsupervised method for learning object categories from interest point features and it was implemented based on Niebles et al. (Niebles et al., 2008). Histogram features of training or testing samples are concatenated to form a co-occurrence matrix which is an input of the pLSA algorithm.
