Generative & discriminative models for classifying social images on the MICC-Flickr101 dataset
Our paper “Combining Generative and Discriminative Models for Classifying Social Images from 101 Object Categories” has been accepted at ICPR’12. We use a hybrid generative-discriminative approach (LDA + SVM with non-linear kernels) over several visual descriptors (SIFT, GIST, colorSIFT).
A major contribution of our work is also the introduction of a novel dataset, called MICC-Flickr101, based on the popular Caltech 101 and collected from Flickr. We demonstrate the effectiveness and efficiency of our method testing it on both datasets, and we evaluate the impact of combining image features and tags for object recognition.