Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
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Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
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In this paper, we propose a novel image classification method based on saliency region and multi-task learning (MTL). The proposed method has the advantages of both region-based and MTL-based methods. Specifically, we first detect the object region of an image with saliency detection technique, then extract its visual features, and then cluster them into groups, and finally employ MTL and SVM to build the classifier. Experimental results on two popular data sets (Corel and Caltech 101) have shown that our method has satisfactory classification performances and outperforms the traditional methods employing only region information or MTL.