Region-based automatic web image selection
Keiji Yanai, Kobus Barnard · 2010
We propose a new Web image selection method which employs the region-based bag-of-features representation. The contribution of this work is (1) to introduce the region-based bag-of-features representation into an Web image selection task where training data is incomplete, and (2) to prove its effectiveness by experiments with both generative and discriminative machine learning methods. In the experiments, we used a multiple-instance learning SVM and a standard SVM as discriminative methods, and pLSA and LDA mixture models as probabilistic generative methods.