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The problem of cross-modal retrieval from multimedia repositories is considered. This problem addresses the design of retrieval systems that support queries across content modalities, for example, using an image to search for texts. A mathematical formulation is proposed, equating the design of cross-modal retrieval systems to that of isomorphic feature spaces for different content modalities. Two...
Automatic image tagging (AIT) is an effective technology to facilitate the process of image retrieval without requiring user to provide a retrieval instance beforehand. In this paper, we propose an AIT method based on kernel canonical correlation analysis (KCCA) with similarity refinement (KCCSR). As a statistic correlation technique, the KCCA aims at extracting some kind of hidden information shared...
Content-based multimedia retrieval faces many challenges such as semantic gap, imbalanced data, and varied qualities of the media. Feature selection as a component of the retrieval process plays an important role. The aim of feature selection is to identify a subset of features by removing irrelevant or redundant features. An effective subset of features can not only improve model performance and...
Most of current researches about 3D model retrieval, one important part of multimedia information retrieval, are mainly in the shape-based way. However, their effects are not satisfactory. This paper proposes a semantic-based 3D model retrieval method which uses the semantic correlations among 3D models to assist automatic annotation and semantic classification. Firstly we measure each model's semantic...
A central debate in visual perception theory is the argument for indirect versus direct perception; i.e., the use of intermediate, abstract, and hierarchical representations versus direct semantic interpretation of images through interaction with the outside world. We present a content-based representation that combines both approaches. The previously developed Visual Alphabet method is extended with...
at the present time, the increase of e-mail spam are heavy to cumber and the spam are vastly spread. These spams cause various problems to the Internet users, such as full incoming mailbox, and wasting time. Therefore, tremendous methods have been proposed but most of them have limitation in the mapping feature and processing time. This paper proposed a method that can detect a set of image e-mail...
A correlation-enhanced similarity matching framework for medical image retrieval is presented in a local concept-based feature space. In this framework, images are presented by vectors of concepts that comprise of local color and texture patches of image regions in a multi-dimensional feature space. To generate the concept vocabularies and represent the images, statistical models are built using a...
Automatic image annotation has become an important and challenging problem due to the existence of semantic gap. In this paper, we firstly extend probabilistic latent semantic analysis (PLSA) to model continuous quantity. In addition, corresponding Expectation-Maximization (EM) algorithm is derived to determine the model parameters. Furthermore, in order to deal with the data of different modalities...
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