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Object-based image retrieval has been an active research topic in the last decade, in which a user is only interested in some object instead of the whole image. As a promising approach, graph-based multi-instance learning has been paid much attention. Early retrieval methods often conduct learning on one graph in either image or region level. To further improve the performance, some recent methods...
State-of-the-art near-duplicate image retrieval systems take the image as a whole by the bag-of-words (BOW) representation. Feature quantization on large image database always reduces the discriminative power of image features, and the global BOW feature neglects the geometric relationships among local features. We propose in this paper a region-based image retrieval method. Image similarity is determined...
Object-based image retrieval has been an active research topic in recent years, in which user only pays his attention to some object in the images. As one promising approach, multiple-instance learning has attracted many researchers. Most of recently proposed methods either need additional restrictions for instance selection or lead to heavy computational load, so that they are often inconvenient...
A new 3D object retrieval approach is proposed based on a novel Bayesian networks lightfield descriptor (BLD). To overcome the disadvantages of the existing 3D object retrieval methods, firstly, we explore Bayesian network for building a new lightfield descriptor, 3D object is put into lightfield, and multi-views information can be obtained along a sphere, and then features of images can be extracted...
Label propagation and manifold ranking have been successfully adopted in content-based image retrieval (CBIR) in recent years. However, while the global low-level features are widely utilized in current systems, region-based features have received little attention. In this paper, a novel transductive framework based on correlated probabilistic label propagation is proposed for region-based images...
To bridge the gap between high level semantic concepts and low level visual features in content-based image retrieval (CBIR), online feature selection is really required. An effective similarity-based online feature selection algorithm in region-based image retrieval (RBIR) systems was proposed by W. Jiang etc., but some parts of the algorithm need to be improved. In this paper, the above algorithm...
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