Name
Abstract | ||
|---|---|---|
We are living in an Age of Information where the amount of accessible data from science and culture is almost limitless. However, this also means that finding an item of interest is increasingly difficult, a digital needle in the proverbial haystack. In this article, we focus on the topic of content-based image retrieval using interactive search techniques, i.e., how does one interactively find any kind of imagery from any source, regardless of whether it is photographic, MRI or X-ray? We highlight trends and ideas from over 170 recent research papers aiming to capture the wide spectrum of paradigms and methods in interactive search, including its subarea relevance feedback. Furthermore, we identify promising research directions and several grand challenges for the future. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/s13735-012-0014-4 | IJMIR |
Keywords | Field | DocType |
Multimedia information retrieval, Content-based image retrieval, Image search, Interactive search, Relevance feedback, Human–computer interaction | Relevance feedback,Haystack,Human–computer information retrieval,Information retrieval,Computer science,Multimedia information retrieval,Image retrieval,Grand Challenges,Content-based image retrieval,Visual Word | Journal |
Volume | Issue | ISSN |
1 | 2 | 2192-662X |
Citations | PageRank | References |
48 | 0.96 | 166 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bart Thomee | 1 | 773 | 39.96 |
| Michael S. Lew | 2 | 2742 | 166.02 |