- Title
- Relevance feature mapping for content-based multimedia information retrieval
- Creator
- Zhou, Guang; Ting, Kaiming; Liu, Fei; Yin, Yilong
- Date
- 2012
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/41067
- Identifier
- vital:6424
- Identifier
- ISSN:0031-3203
- Abstract
- This paper presents a novel ranking framework for content-based multimedia information retrieval (CBMIR). The framework introduces relevance features and a new ranking scheme. Each relevance feature measures the relevance of an instance with respect to a profile of the targeted multimedia database. We show that the task of CBMIR can be done more effectively using the relevance features than the original features. Furthermore, additional performance gain is achieved by incorporating our new ranking scheme which modifies instance rankings based on the weighted average of relevance feature values. Experiments on image and music databases validate the efficacy and efficiency of the proposed framework.
- Relation
- Pattern Recognition Vol. 45, no. 4 (2012), p. 1707-1720
- Rights
- Copyright Pergamon
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0801 Artificial Intelligence and Image Processing; 0899 Other Information and Computing Sciences; 0906 Electrical and Electronic Engineering; Content-based multimedia information retrieval; Ranking; Relevance feature; Relevance feedback; Isolation forest
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