This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Search for Publication

Year(s) from:  to 
Keywords (separated by spaces):

SURF: Speeded Up Robust Features

Herbert Bay, Tinne Tuytelaars, Luc Van Gool
Proceedings of the ninth European Conference on Computer Vision
May 2006


In this paper, we present a novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features). It approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster. This is achieved by relying on integral images for image convolutions; by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a distribution-based descriptor); and by simplifying these methods to the essential. This leads to a combination of novel detection, description, and matching steps. The paper presents experimental results on a standard evaluation set, as well as on imagery obtained in the context of a real-life object recognition application. Both show SURF's strong performance.

Download in pdf format
  author = {Herbert Bay and Tinne Tuytelaars and Luc Van Gool},
  title = {SURF: Speeded Up Robust Features},
  booktitle = {Proceedings of the ninth European Conference on Computer Vision},
  year = {2006},
  month = {May},
  keywords = {}