Deep networks for image retrieval on large-scale databases

ABSTRACT

Currently there are hundreds of millions (high-quality) images in online image repositories such as Flickr. This makes is necessary to develop new algorithms that allow for searching and browsing in those large-scale databases. In this work we explore deep networks for deriving a low-dimensional image representation appropriate for image retrieval. A deep network consisting of multiple layers of features aims to capture higher order correlations between basic image features. We will evaluate our approach on a real world large-scale image database and compare it to image representations based on topic models. Our results show the suitability of the approach for very large databases.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.4 Applications

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing

General Terms:
Algorithms, Experimentation

Keywords:
deep networks, image retrieval