It's all about the data

Tamara L. Berg, Alexander Sorokin, Gang Wang, David Alexander Forsyth, Derek Hoiem, Ian Endres, Ali Farhadi

Research output: Contribution to journalArticlepeer-review


Modern computer vision research consumes labelled data in quantity, and building datasets has become an important activity. The Internet has become a tremendous resource for computer vision researchers. By seeing the Internet as a vast, slightly disorganized collection of visual data, we can build datasets. The key point is that visual data are surrounded by contextual information like text and HTML tags, which is a strong, if noisy, cue to what the visual data means. In a series of case studies, we illustrate how useful this contextual information is. It can be used to build a large and challenging labelled face dataset with no manual intervention. With very small amounts of manual labor, contextual data can be used together with image data to identify pictures of animals. In fact, these contextual data are sufficiently reliable that a very large pool of noisily tagged images can be used as a resource to build image features, which reliably improve on conventional visual features. By seeing the Internet as a marketplace that can connect sellers of annotation services to researchers, we can obtain accurately annotated datasets quickly and cheaply. We describe methods to prepare data, check quality, and set prices for work for this annotation process. The problems posed by attempting to collect very big research datasets are fertile for researchers because collecting datasets requires us to focus on two important questions: What makes a good picture? What is the meaning of a picture?

Original languageEnglish (US)
Article number5464301
Pages (from-to)1434-1452
Number of pages19
JournalProceedings of the IEEE
Issue number8
StatePublished - Aug 2010


  • Computer vision
  • Internet

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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