Abstract
This paper puts forward a novel cross-media retrieval approach, which can process multimedia data of different modalities and measure cross-media similarity, such as image-audio similarity. Both image and audio data are selected for experiments and comparisons. Given the same visual and auditory features the new approach outperforms ICA, PCA and PLS methods both in precision and recall performance. Overall cross-media retrieval results between images and audios are very encouraging.
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