Learning group-based dictionaries for discriminative image representation
A visual concept network is built to characterize the inter-concept correlations. An automatic algorithm is proposed for identifying the visually similar groups. A new algorithm is developed to learn group-based discriminative dictionaries. A structural method is developed for classifier training and image classification. Our proposed algorithms are evaluated on multiple popular visual benchmarks.
discriminative image representation image classification group-based dictionary learning bag-of-visual-words structural learning