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Online Matrix Factorization for Multimodal Image Retrieval
[chapter]
2012
Lecture Notes in Computer Science
In this paper, we propose a method to build an index for image search using multimodal information, that is, using visual features and text data simultaneously. The method combines both data sources and generates one multimodal representation using latent factor analysis and matrix factorization. One remarkable characteristic of this multimodal representation is that it connects textual and visual content allowing to solve queries with only visual content by implicitly completing the missing
doi:10.1007/978-3-642-33275-3_42
fatcat:d3h2huf36bbjtnxvkxgxaawayq