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Yimin Yang , Florida International University, Miami
Hsin-Yu Ha , Florida International University, Miami
Fausto Fleites , Florida International University, Miami
Shu-Ching Chen , Florida International University, Miami
ABSTRACT
We propose a multimedia semantic retrieval system based on Hidden Coherent Feature Groups (HCFGs) to support multimedia semantic retrieval on mobile applications. The system is able to capture the correlation between features and partition the original feature set into HCFGs, which have strong intra-group correlation while maintaining low inter-correlation. Specifically, a feature similarity matrix is built using correlation information between feature pairs, and the Affinity Propagation algorithm is applied to identify the HCFGs, each of which is modeled by one or more classification methods. A novel, multi-model fusion scheme is presented to effectively fuse the multi-model results and generate the final ranked retrieval results. In addition, to incorporate user interaction for effective retrieval, the proposed system also features a user feedback mechanism to refine the retrieval results. Experimental results demonstrate the effectiveness of the proposed framework.
INDEX TERMS
Multimedia communication, Correlation, Feature extraction, Semantics, Hidden Markov models, Training, Mobile communication
CITATION
Yimin Yang, Hsin-Yu Ha, Fausto Fleites, Shu-Ching Chen, "A Multimedia Semantic Retrieval Mobile System Based On Hidden Coherent Feature Groups", IEEE MultiMedia, , no. 1, pp. 1, PrePrints PrePrints, doi:10.1109/MMUL.2013.33
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