Query difficulty estimation for image retrieval
β Scribed by Yangxi Li; Bo Geng; Linjun Yang; Chao Xu; Wei Bian
- Book ID
- 116764402
- Publisher
- Elsevier Science
- Year
- 2012
- Tongue
- English
- Weight
- 610 KB
- Volume
- 95
- Category
- Article
- ISSN
- 0925-2312
No coin nor oath required. For personal study only.
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## Abstract Traditional contentβbased image retrieval (CBIR) systems find relevant images close to an example image. This singleβpoint model has been shown inadequate for complex queries built on highβlevel concepts. Recent CBIR systems allow users to use multiple examples to compose their queries.
are typically generated manually by human beings, they We present a two-pass image retrieval system in which re-provide compact, important [8], though sometimes biased trieval techniques for text and image documents are combined and incomplete, descriptions of the visual content. Such in a novel app