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Semantic Boosting Cross-Modal Hashing for efficient multimedia retrieval.
- Source :
-
Information Sciences . Feb2016, Vol. 330, p199-210. 12p. - Publication Year :
- 2016
-
Abstract
- Cross-modal hashing aims to embed data from different modalities into a common low-dimensional Hamming space, which serves as an important part in cross-modal retrieval. Although many linear projection methods were proposed to map cross-modal data into a common abstract space, the semantic similarity between cross-modal data was often ignored. To address this issue, we put forward a novel cross-modal hashing method named Semantic Boosting Cross-Modal Hashing (SBCMH). To preserve the semantic similarity, we first apply multi-class logistic regression to project heterogeneous data into a semantic space, respectively. To further narrow the semantic gap between different modalities, we then use a joint boosting framework to learn hash functions, and finally transform the mapped data representations into a measurable binary subspace. Comparative experiments on two public datasets demonstrate the effectiveness of the proposed SBCMH. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00200255
- Volume :
- 330
- Database :
- Academic Search Index
- Journal :
- Information Sciences
- Publication Type :
- Periodical
- Accession number :
- 111321456
- Full Text :
- https://doi.org/10.1016/j.ins.2015.10.028