Latent semantic fusion model for image retrieval and annotation

This paper studies the effect of Latent Semantic Analysis (LSA) on two different tasks: multimedia document retrieval (MDR) and automatic image annotation (AIA). The contributions of this paper are twofold. First, to the best of our knowledge, this work is the first study of the influence of LSA on the retrieval of a significant number of multimedia documents (i.e. collection of 20000 tourist images). Second, it shows how different image representations (region-based and keypoint-based) can be combined by LSA to improve automatic image annotation. The document collections used for these experiments are the Corel photo collection and ImageCLEF 2006 collection. Categories and Subject Descriptors H.3.1 [Information Systems]: Information Storage and Retrieval—content analysis and indexing General Terms Algorithm Keywords image indexing and retrieval, automatic annotation, latent semantic indexing, multimedia fusion

• Type: Conference
• Year: 2007
• Where: CIKM
• Authors: Trong-Ton Pham, Nicolas Maillot, Joo-Hwee Lim, Jean-Pierre Chevallet
• Keywords: Automatic Image Annotation, CIKM 2007, Multimedia Document Retrieval, Multimedia Documents