A comprehensive review of current local features for computer vision

  • Authors:

  • Jing Li;Nigel M. Allinson

  • Affiliations:

  • Vision and Information Engineering Research Group, Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, S1 3JD, UK;Vision and Information Engineering Research Group, Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, S1 3JD, UK

  • Venue:
  • Neurocomputing
  • Year:
  • 2008

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Abstract

Local features are widely utilized in a large number of applications, e.g., object categorization, image retrieval, robust matching, and robot localization. In this review, we focus on detectors and local descriptors. Both earlier corner detectors, e.g., Harris corner detector, and later region detectors, e.g., Harris affine region detector, are described in brief. Most kinds of descriptors are described and summarized in a comprehensive way. Five types of descriptors are included, which are filter-based descriptors, distribution-based descriptors, textons, derivative-based descriptors and others. Finally, the matching methods and different applications with respect to the local features are also mentioned. The objective of this review is to provide a brief introduction for new researchers to the local feature research field, so that they can follow an appropriate methodology according to their specific requirements.